國立中央大學教師履歷平台

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陳彥良

Chen, Yen-Liang

ylchen@mgt.ncu.edu.tw

國科會計畫統計

考慮關聯性、新奇性、購物籃大小的循序推薦
1150801~1160731
考慮關聯性、新奇性、購物籃大小的循序推薦
1140801~1150731
以深度學習為基的推薦系統
1140801~1150731
考慮關聯性、新奇性、購物籃大小的循序推薦
1130801~1140731
以深度學習為基的推薦系統
1130801~1140731
以深度學習為基的推薦系統
1120801~1130731
三個推薦系統的擴增與改進
1120801~1130731
[推薦,協同推薦,深度學習模型,時間衰殘,跨平台推薦 , Recommendation,collaborative recommendation,deep learning model,time decay,cross-platform recommendation]
使用多種圖編碼進行鏈結預測
1110801~1120731
[鏈結預測,網絡嵌入,集成學習,深度神經網路 , Link prediction,Ensemble　learning,Graph　 embedding,Deep Neural Network]
三個推薦系統的擴增與改進
1110801~1120731
[推薦,協同推薦,深度學習模型,時間衰殘,跨平台推薦 , Recommendation,collaborative recommendation,deep learning model,time decay,cross-platform recommendation]
一個面向等級的情緒分析深度學習方法
1100801~1110731
[情感分析、深度學習、文字嵌入、自我注意力、構件聚焦 , Sentiment analysis,deep learning,word embedding,self-attention,component focusing]
三個推薦系統的擴增與改進
1100801~1110731
[推薦,協同推薦,深度學習模型,時間衰殘,跨平台推薦 , Recommendation,collaborative recommendation,deep learning model,time decay,cross-platform recommendation]
在成本/資源限制下選擇資料進行標註
1090801~1100731
[分類,非監督式樣本選取,成本,資源,分類器 , Classification,Unsupervised instance selection,Cost,Resource,Classifiers]
在成本/資源限制下選擇資料進行標註
1080801~1090731
[分類,非監督式樣本選取,成本,資源,分類器 , Classification,Unsupervised instance selection,Cost,Resource,Classifiers]
具最小歸納成本之屬性導向歸納法
1070801~1080731
[屬性導向歸納法,分群演算法,基因演算法,貪婪演算法,一般化表格 , Attribute-Oriented Induction,Clustering,Genetic algorithm (GA),Greedy Algorithm, Generalized Table]
在成本/資源限制下選擇資料進行標註
1070801~1080731
[分類,非監督式樣本選取,成本,資源,分類器 , Classification,Unsupervised instance selection,Cost,Resource,Classifiers]
具最小歸納成本之屬性導向歸納法
1060801~1070731
[屬性導向歸納法,分群演算法,基因演算法,貪婪演算法,一般化表格 , Attribute-Oriented Induction,Clustering,Genetic algorithm (GA),Greedy Algorithm, Generalized Table]
多準則決策表格的摘要化方法
1060801~1070731
[多準則決策模型,決策表,基因演算法,貪婪演算法,求解空間 , Multi-criteria decision making model, Decision table, Genetic algorithm (GA), Greedy algorithm, Solution space]
具最小歸納成本之屬性導向歸納法
1050801~1060731
[屬性導向歸納法,分群演算法,基因演算法,貪婪演算法,一般化表格 , Attribute-Oriented Induction,Clustering,Genetic algorithm (GA),Greedy Algorithm, Generalized Table]
多準則決策表格的摘要化方法
1050801~1060731
[多準則決策模型,決策表,基因演算法,貪婪演算法,求解空間 , Multi-criteria decision making model, Decision table, Genetic algorithm (GA), Greedy algorithm, Solution space]
多準則決策表格的摘要化方法
1040801~1050731
[多準則決策模型,決策表,基因演算法,貪婪演算法,求解空間 , Multi-criteria decision making model, Decision table, Genetic algorithm (GA), Greedy algorithm, Solution space]

期刊著作

A3BRec: A Novel Association-Integration Sequential Basket Recommendation
IEEE Transactions on Knowledge and Data Engineering, 38, 2, 800-813, 2026-01-01
[ Association rule,deep learning,recommendation system,transformer ]
Using large multimodal models to predict outfit compatibility
Decision Support Systems, 194, 2025-07-01
[ Large language models,Large multi-modal models,Outfit compatibility,Outfit recommendation ]
PIFTA4Rec: leveraging personalized item frequency and temporal attention for enhanced next-basket recommendation
Journal of Supercomputing, 81, 8, 2025-06-01
[ Deep learning,Item2Vec,K nearest neighbor,Next-basket recommendation,Personalized item frequency ]
G-TransRec: A Transformer-Based Next-Item Recommendation With Time Prediction
IEEE Transactions on Computational Social Systems, 11, 3, 4175-4188, 2024-06-01
[ Deep learning,item and time prediction,neural network,sequential recommendation,transformer ]
Using personalized next session to improve session-based recommender systems
Journal of Supercomputing, 80, 6, 7369-7398, 2024-04-01
[ Deep learning,Global information,Neural network,Personalized recommendation,Session embedding,Session-based recommendation ]
A Deep Recommendation Model Considering the Impact of Time and Individual Diversity
IEEE Transactions on Computational Social Systems, 11, 2, 2558-2569, 2024-04-01
[ Attention mechanism,bidirectional encoder representation from transformers (BERT) model,deep learning,recommendation system,time decay ]
A novel virtual-communicated evolution learning recommendation
Industrial Management and Data Systems, 124, 1, 416-441, 2024-01-02
[ Deep learning,Long short-term memory,Matrix factorization,Recommendation system ]
A deep multi-embedding model for mobile application recommendation
Decision Support Systems, 173, 2023-10-01
[ Deep learning,Matrix factorization,Multi-embedding,Neural networks,Recommender system ]
A cross-platform recommendation system from Facebook to Instagram
Electronic Library, 41, 2-3, 264-285, 2023-05-24
[ Cross-platform recommendation system,Facebook,Instagram,Social media ]
對「漫談學術生涯：機會、創新與滿意度」回應 Response to ＂On Academic Life: Opportunities, Innovation, and Satisfaction＂
管理學報, 39, 3, 289-292, 2022-09-01
[ 機會,創新 ]
Aspect-based sentiment analysis with component focusing multi-head co-attention networks
Neurocomputing, 489, 9-17, 2022-06-07
[ BERT,Deep learning,Neural network,Sentiment analysis ]
An ensemble model for link prediction based on graph embedding
Decision Support Systems, 157, 2022-06-01
[ Ensemble learning,Graph embedding,Link prediction ]
MK-Means: Detecting evolutionary communities in dynamic networks
Expert Systems with Applications, 176, 2021-08-15
[ Clustering,Evolutionary clustering,K-Means,Social community ]
Noise-free attribute-oriented induction
Information Sciences, 568, 333-349, 2021-08-01
[ Attribute-Oriented Induction,Concept Hierarchy,Data mining,Noise ]
Predicting ewom’s influence on purchase intention based on helpfulness, credibility, information quality and professionalism
Sustainability, 13, 13, 2021-07-01
[ Credibility,Electronic word-of-mouth (eWOM),Helpfulness,Information quality,Professionalism,Purchase intention ]
A movie recommendation method based on users' positive and negative profiles
Information Processing and Management, 58, 3, 2021-05-01
[ Collaborative filtering,Hybrid recommendation,Recommendation,User profile ]
A template approach for summarizing restaurant reviews
IEEE Access, 9, 115548-115562, 2021-01-01
[ Restaurant reviews,sentiment analysis,summarization,template,TextRank ]
Building a training dataset for classification under a cost limitation
Electronic Library, 39, 1, 77-96, 2021-01-01
[ Big data,Classification,Data mining,Text mining ]
Summarization of information systems based on rough set theory
Journal of Intelligent and Fuzzy Systems, 40, 1, 1001-1015, 2021-01-01
[ Attribute reduction,Information system,Reduct,Rough set,Summarization ]
Mining specific and representative information by the attribute-oriented induction method
Expert Systems, 2020-01-01
[ attribute-oriented induction,concept hierarchy,cost,data mining,noise ]
Early prediction of the future popularity of uploaded videos
Expert Systems with Applications, 133, 59-74, 2019-11-01
[ Data mining , Popularity prediction , YouTube ]
Cost-sensitive decision tree with multiple resource constraints
Applied Intelligence, 49, 10, 3765-3782, 2019-10-01
[ Cost-sensitive learning , Data mining , Decision tree , Machine Learning ]
An innovative citation recommendation model for draft papers with varying degrees of information completeness
Data Technologies and Applications, 53, 4, 562-576, 2019-09-03
[ Citation , Draft paper , Incompleteness , Recommendation system , Text mining , WordNet ]
A two-phase sentiment analysis approach for judgement prediction
Journal of Information Science, 44, 5, 594-607, 2018-10-01
[ Criminal precedent , judgement classification , sentiment analysis , support vector machines (SVM) , text mining ]
An analysis of collaborative problem-solving activities mediated by individual-based and collaborative computer simulations
Journal of Computer Assisted Learning, 33, 6, 649-662, 2017-12-01
[ collaborative problem solving , computer simulations , discourse analysis , lag sequential analysis , learning analytics ]
Emotion classification of YouTube videos
Decision Support Systems, 101, 40-50, 2017-09-01
[ Data mining , Machine learning , Sentiments analysis , YouTube ]
A two-stage clustering algorithm for the two-attribute-set problem
Advanced Science Letters, 23, 5, 4258-4262, 2017-05-01
[ Cluster analysis , Clustering , Data mining ]
A two-attributes-set spatial clustering algorithm for geography data
Advanced Science Letters, 23, 5, 3843-3848, 2017-05-01
[ Cluster analysis , Data mining , Spatial clustering ]
Opinion mining from online hotel reviews – A text summarization approach
Information Processing and Management, 53, 2, 436-449, 2017-03-01
[ k-medoids , Multi-text summarization , Online hotel review , Sentence clustering , Sentiment analysis ]
Identifying conflict patterns to reach a consensus - A novel group decision approach
European Journal of Operational Research, 254, 2, 622-631, 2016-10-16
[ Conflict patterns , Data mining , Decision-making , Group decision-making , Maximum consensus sequence ]
Decision tree induction with a constrained number of leaf nodes
Applied Intelligence, 45, 3, 673-685, 2016-10-01
[ Classification , Constraint tree , Data mining , Decision tree ]
A novel recommendation model with Google similarity
Decision Support Systems, 89, 17-27, 2016-09-01
[ Collaborative filtering , Data mining , Normalized Google distance , Recommender system ]
Time-constrained cost-sensitive decision tree induction
Information Sciences, 354, 140-152, 2016-08-01
[ Classification , Cost-sensitive learning , Data mining , Decision analysis , Decision tree ]
A novel approach to rate and summarize online reviews according to user-specified aspects
Journal of Electronic Commerce Research, 17, 2, 132-152, 2016-05-01
[ K-means , Normalized google distance , Online reviews , Opinion mining , Sentiment analysis ]
A novel summarization technique for the support of resolving multi-criteria decision making problems
Decision Support Systems, 79, 109-124, 2015-11-01
[ Decision table , Genetic algorithm , Multi-criteria decision making , Summarization ]
An annotation approach to contextual advertising for online ADS
Journal of Electronic Commerce Research, 16, 2, 123-137, 2015-01-01
[ Annotation , Contextual advertising , Online advertisements , Recommendation , Tag ]
Predicting associated statutes for legal problems
Information Processing and Management, 51, 1, 194-211, 2015-01-01
[ (NGD) , (SVM) , Apriori algorithm , Criminal judgment , Distance , Google , Normalized , Statute , Support vector machines , Text mining ]
Predicting the influence of users' posted information for eWOM advertising in social networks
Electronic Commerce Research and Applications, 13, 6, 431-439, 2014-01-01
[ Data mining , Electronic word-of-mouth (eWOM) , Influence , Sentiment analysis , Social network ]
Community detection based on social interactions in a social network
Journal of the Association for Information Science and Technology, 65, 3, 539-550, 2014-01-01
Cross-language patent matching via an international patent classification-based concept bridge
Journal of Information Science, 39, 6, 737-753, 2013-12-01
[ cross-language patent matching , latent semantic indexing , patent mining ]
A new approach to the group ranking problem: Finding consensus ordered segments from users' preference data
Decision Sciences, 44, 6, 1091-1119, 2013-12-01
[ Artificial Intelligence , Cluster Analysis , Collaborative Decision Models , Group Decision Support , Group/Team Decision Making ]
A novel decision-tree method for structured continuous-label classification
IEEE Transactions on Cybernetics, 43, 6, 1734-1746, 2013-12-01
[ Classification algorithms , Data mining , Decision trees (DTs) ]
A text mining approach to assist the general public in the retrieval of legal documents
Journal of the American Society for Information Science and Technology, 64, 2, 280-290, 2013-02-01
[ information retrieval , text mining ]
Conjecturable knowledge discovery: A fuzzy clustering approach
Fuzzy Sets and Systems, 221, 1-23, 2013-01-22
[ Classification , Conjecturable rules , Data mining , Fuzzy clustering ]
Mining consensus preference graphs from users' ranking data
Decision Support Systems, 54, 2, 1055-1064, 2013-01-01
[ Data mining , Decision making , Group decision making , Maximum consensus sequence , Preference graph ]
A three-phase method for patent classification
Information Processing and Management, 48, 6, 1017-1030, 2012-11-01
[ IPC taxonomy , K nearest neighbors (KNN) , K-means , Patent classification , Support vector machines (SVM) , Vector space model (VSM) ]
Vector space model for patent documents with hierarchical class labels
Journal of Information Science, 38, 3, 222-233, 2012-06-01
[ document classification , feature selection , hierarchical class label , vector space model (VSM) ]
From data to global generalized knowledge
Decision Support Systems, 52, 2, 295-307, 2012-01-01
[ Attribute-oriented induction , Data mining , Generalized knowledge , Multiple-level mining ]
An evolutionary PageRank approach for journal ranking with expert judgements
Journal of Information Science, 37, 3, 254-272, 2011-06-01
[ citation-based approach , experts' survey method , journal ranking , PageRank , Particle Swarm Optimization ]
An IPC-based vector space model for patent retrieval
Information Processing and Management, 47, 3, 309-322, 2011-05-01
[ Patent mining , Patent retrieval , Vector space model (VSM) ]
Mining negative generalized knowledge from relational databases
Knowledge-Based Systems, 24, 1, 134-145, 2011-02-01
[ Attribute-oriented induction , Data mining , Generalized knowledge , Multiple-level mining , Negative pattern ]
Discovering multi-label temporal patterns in sequence databases
Information Sciences, 181, 3, 398-418, 2011-02-01
[ Interval-based event sequence , Point-based event sequence , Sequential patterns , Temporal patterns ]
Mining associative classification rules with stock trading data-A GA-based method
Knowledge-Based Systems, 23, 6, 605-614, 2010-08-01
[ Associative classification rules , Data mining , Genetic algorithm , Numerical data ]
Mining fuzzy association rules from uncertain data
Knowledge and Information Systems, 23, 2, 129-152, 2010-05-01
[ Data mining , Fuzzy association rules , Fuzzy statistics and data analysis , Learning , Uncertain data ]
An approach to group ranking decisions in a dynamic environment
Decision Support Systems, 48, 4, 622-634, 2010-03-01
[ Data mining , Group decision making , Group ranking , Maximum consensus sequence ]
Gene clustering by using query-based self-organizing maps
Expert Systems with Applications, 37, 9, 6689-6694, 2010-01-01
[ Bioinformatics , Data clustering , Data mining , Gene expression , Microarray analysis , Neural networks , Query-based learning , Self-organizing maps ]
Mining sequential patterns in the B2B environment
Journal of Information Science, 35, 6, 677-694, 2009-12-01
[ Business-to-business , Data mining , Sequential pattern ]
Discovering hybrid temporal patterns from sequences consisting of point- and interval-based events
Data and Knowledge Engineering, 68, 11, 1309-1330, 2009-11-01
[ Data mining , Hybrid event sequences , Hybrid temporal pattern , Sequential pattern , Temporal pattern ]
A dynamic discretization approach for constructing decision trees with a continuous label
IEEE Transactions on Knowledge and Data Engineering, 21, 11, 1505-1514, 2009-11-01
[ Classification. , Data mining , Decision trees ]
Discovering recency, frequency, and monetary (RFM) sequential patterns from customers' purchasing data
Electronic Commerce Research and Applications, 8, 5, 241-251, 2009-10-01
[ Constraint-based mining , RFM , Segmentation , Sequential pattern ]
Mining maximum consensus sequences from group ranking data
European Journal of Operational Research, 198, 1, 241-251, 2009-10-01
[ Data mining , Decision making , Group decision making , Maximum consensus sequence ]
On mining multi-time-interval sequential patterns
Data and Knowledge Engineering, 68, 10, 1112-1127, 2009-10-01
[ Data mining , Knowledge discovery , Multi-time-interval , Sequential pattern , Time-interval ]
Building a cost-constrained decision tree with multiple condition attributes
Information Sciences, 179, 7, 967-979, 2009-03-15
[ Classification , Cost-sensitive learning , Data mining , Decision analysis , Decision tree ]
Constructing a decision tree from data with hierarchical class labels
Expert Systems with Applications, 36, 3 PART 1, 4838-4847, 2009-01-01
[ Classification , Decision tree , Hierarchical class label ]
A phenotypic genetic algorithm for inductive logic programming
Expert Systems with Applications, 36, 3 PART 2, 6935-6944, 2009-01-01
[ Inductive logic programming , Multiple level structure , Numerical data , Phenotypic genetic algorithm , Semantic roles ]
Mining fuzzy association rules from questionnaire data
Knowledge-Based Systems, 22, 1, 46-56, 2009-01-01
[ Association rules , Data mining , Fuzzy sets , Questionnaire data ]
Using decision trees to summarize associative classification rules
Expert Systems with Applications, 36, 2 PART 1, 2338-2351, 2009-01-01
[ Decision trees , Rule summarization , Rule-based classification ]
Mining typical patterns from databases
Information Sciences, 178, 19, 3683-3696, 2008-10-01
[ Clustering , Data mining , Typical patterns mining ]
A novel knowledge discovering model for mining fuzzy multi-level sequential patterns in sequence databases
Data and Knowledge Engineering, 66, 3, 349-367, 2008-09-01
[ Data mining , Fuzzy sets , Multi-level , Sequence data , Sequential patterns ]
A novel collaborative filtering approach for recommending ranked items
Expert Systems with Applications, 34, 4, 2396-2405, 2008-05-01
[ Collaborative filtering , Ranking list , Recommender system ]
A novel approach for discovering retail knowledge with price information from transaction databases
Expert Systems with Applications, 34, 4, 2350-2359, 2008-05-01
[ Association rules , Data mining , Price , Retailing management ]
A Petri net approach to support resource assignment in project management
IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans, 38, 3, 564-574, 2008-05-01
[ Object composition Petri net (OCPN) , Petri nets , Project management , Resource assignment , Resource sharing ]
Context-based market basket analysis in a multiple-store environment
Decision Support Systems, 45, 1, 150-163, 2008-04-01
[ Algorithm , Association rule , Data mining , Store chain ]
A group recommendation system with consideration of interactions among group members
Expert Systems with Applications, 34, 3, 2082-2090, 2008-04-01
[ Collaborative filtering , Genetic algorithm , Group recommender system ]
Mining association rules from imprecise ordinal data
Fuzzy Sets and Systems, 159, 4, 460-474, 2008-02-16
[ Association rules , Data mining , Imprecise ordinal data ]
A dynamic-programming algorithm for hierarchical discretization of continuous attributes
European Journal of Operational Research, 184, 2, 636-651, 2008-01-16
[ Concept hierarchy , Continuous data , Data mining , Dynamic programming ]
Ranking Taiwanese management journals: A case study
Scientometrics, 76, 1, 95-115, 2008-01-01
Using position, fonts and cited references to retrieve scientific documents
Journal of Information Science, 33, 4, 492-508, 2007-08-01
[ Cited reference , Features , Font , Information retrieval , Position , Scientific documents , Text ]
Mining nonambiguous temporal patterns for interval-based events
IEEE Transactions on Knowledge and Data Engineering, 19, 6, 742-758, 2007-06-01
[ Data mining , Interval-based events , Sequential patterns , Temporal pattern ]
A petri net model with time window constraints
Journal of the Chinese Institute of Industrial Engineers, 24, 2, 110-119, 2007-01-01
[ Petri net , Resource , Time-window ]
A data mining approach for retail knowledge discovery with consideration of the effect of shelf-space adjacency on sales
Decision Support Systems, 42, 3, 1503-1520, 2006-12-01
[ Association rules , Data mining , Merchandising , Retailing management , Shelf-space management ]
Constraint-based sequential pattern mining: The consideration of recency and compactness
Decision Support Systems, 42, 2, 1203-1215, 2006-11-01
[ Constraint-based mining , Sequential pattern , Temporal database ]
TASC: Two-attribute-set clustering through decision tree construction
European Journal of Operational Research, 174, 2, 930-944, 2006-10-16
[ Clustering , Data mining , Decision tree ]
Mining association rules with multiple minimum supports: a new mining algorithm and a support tuning mechanism
Decision Support Systems, 42, 1, 1-24, 2006-10-01
[ Association rules , Data mining , FP-tree , Minimum supports ]
A similarity-based method for retrieving documents from the SCI/SSCI database
Journal of Information Science, 32, 5, 449-464, 2006-10-01
[ Information retrieval , Neural network , Similarity ]
An overlapping cluster algorithm to provide non-exhaustive clustering
European Journal of Operational Research, 173, 3, 762-780, 2006-09-16
[ Data mining , Non-exhaustive clustering , Overlapping clusters , Partitioning clustering ]
A new approach for discovering fuzzy quantitative sequential patterns in sequence databases
Fuzzy Sets and Systems, 157, 12, 1641-1661, 2006-06-16
[ Data mining , Fuzzy sets , Quantitative data , Sequence data , Sequential patterns ]
Mining predecessor-successor rules from DAG data
International Journal of Intelligent Systems, 21, 6, 621-637, 2006-06-01
Finding K shortest looping paths with waiting time in a time-window network
Applied Mathematical Modelling, 30, 5, 458-465, 2006-05-01
[ Shortest looping path , Time-window ]
Discovering conjecturable rules through tree-based clustering analysis
Expert Systems with Applications, 29, 3, 493-505, 2005-10-01
[ Clustering analysis , Conceptual clustering , Conjecturable rules , Data mining , Decision tree ]
Discovering fuzzy time-interval sequential patterns in sequence databases
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 35, 5, 959-972, 2005-10-01
[ Data mining , Fuzzy sets , Sequence data , Sequential patterns , Time interval ]
Mining generalized knowledge from ordered data through attribute-oriented induction techniques
European Journal of Operational Research, 166, 1 SPEC. ISS., 221-245, 2005-10-01
[ Attribute-oriented induction , Concept hierarchy , Data mining , Dynamic programming , Ordered data , Relational data ]
Market basket analysis in a multiple store environment
Decision Support Systems, 40, 2, 339-354, 2005-08-01
[ Algorithm , Association rules , Data mining , Store chain ]
Finding K shortest looping paths in a traffic-light network
Computers and Operations Research, 32, 3, 571-581, 2005-03-01
[ Looping path , Shortest path , Traffic-light ]
Finding the Kth shortest path in a time-schedule network
Naval Research Logistics, 52, 1, 93-102, 2005-02-01
Mining sequential patterns from multidimensional sequence data
IEEE Transactions on Knowledge and Data Engineering, 17, 1, 136-140, 2005-01-01
[ Data mining , Frequent pattern , Sequence data , Sequential patterns ]
The first K shortest unique-arc walks in a traffic-light network
Mathematical and Computer Modelling, 40, 13, 1453-1464, 2004-12-01
[ Shortest path , Traffic-light , Walk ]
Algorithms for mining association rules in bag databases
Information Sciences, 166, 1-4, 31-47, 2004-10-29
[ Association rule , Data mining , Fuzzy set ]
Mining DAG patterns from DAG databases
Lecture Notes in Computer Science, 3129, 579-588, 2004-01-01
Mining inheritance rules from genealogical data
Lecture Notes in Computer Science, 3129, 569-578, 2004-01-01
Finding the first K shortest paths in a time-window network
Computers and Operations Research, 31, 4, 499-513, 2004-01-01
[ Network , Shortest path , Simple path , Time-window constraint ]
Discovering time-interval sequential patterns in sequence databases
Expert Systems with Applications, 25, 3, 343-354, 2003-10-01
[ Data mining , Sequence data , Sequential patterns , Time interval ]
Shipping problems with body clock constraints
Computers and Operations Research, 30, 7, 1037-1049, 2003-06-01
[ Body clock constraint , Network , Shipping , Time-window constraint , Transportation , Vehicle routing ]
Mining inter-organizational retailing knowledge for an alliance formed by competitive firms
Information and Management, 40, 5, 431-442, 2003-05-01
[ Association rules , Data mining , Data warehouse , POS , Retail store ]
Minimization of travel time and weighted number of stops in a traffic-light network
European Journal of Operational Research, 144, 3, 565-580, 2003-02-01
[ Road network , Shortest path , Time window , Traffic light ]
STRPN: A petri-net approach for modeling spatial-temporal relations between moving multimedia objects
IEEE Transactions on Software Engineering, 29, 1, 63-76, 2003-01-01
[ Multimedia , Petri Net , Relative coordination , Spatial-temporal relations , Two-phase firing conditions , Valid firing sequences ]
Constructing a multi-valued and multi-labeled decision tree
Expert Systems with Applications, 25, 2, 199-209, 2003-01-01
[ Classification , Customer relation management , Data mining , Decision tree , Multi-labeled attribute , Multi-valued attribute , Prediction ]
Time analysis for planning a path in a time-window network
Journal of the Operational Research Society, 54, 8, 860-870, 2003-01-01
[ Network , Time analysis , Time-window constraint ]
Mining hybrid sequential patterns and sequential rules
Information Systems, 27, 5, 345-362, 2002-01-01
[ Association rule , Data mining , Pattern , Sequential data ]
The first K minimum cost paths in a time-schedule network
Journal of the Operational Research Society, 52, 1, 102-108, 2001-01-01
[ Networks and graphs , Road transport , Shortest path ]
Finding the critical path in an activity network with time-switch constraints
European Journal of Operational Research, 120, 3, 603-613, 2000-02-01
Shortest paths in traffic-light networks
Transportation Research, Series B: Methodological, 34, 4, 241-253, 2000-01-01
[ Road network , Shortest path , Time window , Traffic light ]
Minimum time paths in a network with mixed time constraints
Computers and Operations Research, 25, 10, 793-805, 1998-01-01
Critical path in an activity network with time constraints
European Journal of Operational Research, 100, 1, 122-133, 1997-07-01
[ Activity network , Critical path , Float time , Longest path , PERT , Time-schedule , Time-window ]
The minimal average cost flow problem
European Journal of Operational Research, 81, 3, 561-570, 1995-03-16
[ Min-cost flow problem , Network flow model ]
A parametric maximum flow algorithm for bipartite graphs with applications
European Journal of Operational Research, 80, 1, 226-235, 1995-01-05
[ Bipartite graph , Maximum flow , Parametric algorithm ]
The hybrid spanning tree problem
European Journal of Operational Research, 77, 1, 179-188, 1994-08-25
[ combinatorial analysis , computational analysis , graphs , minimal spanning tree , Network ]
Finding the k quickest simple paths in a network
Information Processing Letters, 50, 2, 89-92, 1994-04-22
[ Combinatorial problems , Design of algorithms , Shortest and quickest path ]
Scheduling jobs to minimize total cost
European Journal of Operational Research, 74, 1, 111-119, 1994-04-07
[ Deterministic scheduling , Maximum flow problem , Min-cost flow problem ]
An algorithm for finding the k quickest paths in a network
Computers and Operations Research, 20, 1, 59-65, 1993-01-01
The quickest path problem
Computers and Operations Research, 17, 2, 153-161, 1990-01-01
Scheduling unit-time jobs on processors with different capabilities
Computers and Operations Research, 16, 5, 409-417, 1989-01-01

研討會著作

Humanizing Learning with Generative AI: An Intelligent Reading Companion for Personalized and Inclusive Education
2026-03-24
[ Generative AI,Intelligent Learning Companion,Personalized Learning,Inclusive Education ]
A Novel Ensemble Model for Link Prediction in Social Network
2024-10-08
[ ensemble model,Link prediction,regression,social network ]
Classification of time-sequential attributes by using sequential pattern rules
735-739, 2007-12-01
A sampling-based method for mining frequent patterns from databases
536-545, 2005-10-27

專書

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
617-627, 2006-07-07
[ Petri nets,Resource assignment,WF-RAPN,Workflow ]
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
586-595, 2006-01-01
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
536-545, 2006-01-01

校外榮譽

114 [史丹佛大學] 史丹佛大學公布 - 2025全球前2%頂尖科學家(終身影響力)
114 [史丹佛大學] 史丹佛大學公布 - 2025全球前2%頂尖科學家(單年影響力)
113 [國家科學及技術委員會] 國家科學及技術委員會 113 年度傑出特約研究員
113 [史丹佛大學] 史丹福大學公布 - 2024全球前2%頂尖科學家(終身影響力)
113 [史丹佛大學] 史丹福大學公布 - 2024全球前2%頂尖科學家(單年影響力)
112 [史丹佛大學] 史丹福大學公布 - 2023全球前2%頂尖科學家(單年影響力)
112 [史丹佛大學] 史丹福大學公布 - 2023全球前2%頂尖科學家(終身影響力)
111 [史丹佛大學] 史丹福大學公布 - 2022全球前2%頂尖科學家(單年影響力)
111 [史丹佛大學] 史丹福大學公布 - 2022全球前2%頂尖科學家(終身影響力)
110 [史丹佛大學] 史丹福大學公布 - 2021全球前2%頂尖科學家(終身影響力)
110 [史丹佛大學] 史丹福大學公布 - 2021全球前2%頂尖科學家(單年影響力)
107 [科技部] 國科會特約研究員
105 [教育部] 第60屆教育部學術獎
98 [科技部] 傑出研究獎
92 [科技部] 傑出研究獎

校內獲獎

111 資訊管理講座
108 資訊管理講座
105 資訊管理講座

陳彥良

Chen, Yen-Liang

現職

專長

專長簡述

最高學歷

相關連結

科技部學門領域

政府GRB研究專長領域

教育部學門領域

國科會計畫統計

考慮關聯性、新奇性、購物籃大小的循序推薦 1150801~1160731

考慮關聯性、新奇性、購物籃大小的循序推薦 1140801~1150731

以深度學習為基的推薦系統 1140801~1150731

考慮關聯性、新奇性、購物籃大小的循序推薦 1130801~1140731

以深度學習為基的推薦系統 1130801~1140731

以深度學習為基的推薦系統 1120801~1130731

三個推薦系統的擴增與改進 1120801~1130731 [推薦,協同推薦,深度學習模型,時間衰殘,跨平台推薦 , Recommendation,collaborative recommendation,deep learning model,time decay,cross-platform recommendation]

使用多種圖編碼進行鏈結預測 1110801~1120731 [鏈結預測,網絡嵌入,集成學習,深度神經網路 , Link prediction,Ensemble learning,Graph embedding,Deep Neural Network]

三個推薦系統的擴增與改進 1110801~1120731 [推薦,協同推薦,深度學習模型,時間衰殘,跨平台推薦 , Recommendation,collaborative recommendation,deep learning model,time decay,cross-platform recommendation]

一個面向等級的情緒分析深度學習方法 1100801~1110731 [情感分析、深度學習、文字嵌入、自我注意力、構件聚焦 , Sentiment analysis,deep learning,word embedding,self-attention,component focusing]

三個推薦系統的擴增與改進 1100801~1110731 [推薦,協同推薦,深度學習模型,時間衰殘,跨平台推薦 , Recommendation,collaborative recommendation,deep learning model,time decay,cross-platform recommendation]

在成本/資源限制下選擇資料進行標註 1090801~1100731 [分類,非監督式樣本選取,成本,資源,分類器 , Classification,Unsupervised instance selection,Cost,Resource,Classifiers]

在成本/資源限制下選擇資料進行標註 1080801~1090731 [分類,非監督式樣本選取,成本,資源,分類器 , Classification,Unsupervised instance selection,Cost,Resource,Classifiers]

具最小歸納成本之屬性導向歸納法 1070801~1080731 [屬性導向歸納法,分群演算法,基因演算法,貪婪演算法,一般化表格 , Attribute-Oriented Induction,Clustering,Genetic algorithm (GA),Greedy Algorithm, Generalized Table]

在成本/資源限制下選擇資料進行標註 1070801~1080731 [分類,非監督式樣本選取,成本,資源,分類器 , Classification,Unsupervised instance selection,Cost,Resource,Classifiers]

具最小歸納成本之屬性導向歸納法 1060801~1070731 [屬性導向歸納法,分群演算法,基因演算法,貪婪演算法,一般化表格 , Attribute-Oriented Induction,Clustering,Genetic algorithm (GA),Greedy Algorithm, Generalized Table]

多準則決策表格的摘要化方法 1060801~1070731 [多準則決策模型,決策表,基因演算法,貪婪演算法,求解空間 , Multi-criteria decision making model, Decision table, Genetic algorithm (GA), Greedy algorithm, Solution space]

具最小歸納成本之屬性導向歸納法 1050801~1060731 [屬性導向歸納法,分群演算法,基因演算法,貪婪演算法,一般化表格 , Attribute-Oriented Induction,Clustering,Genetic algorithm (GA),Greedy Algorithm, Generalized Table]

多準則決策表格的摘要化方法 1050801~1060731 [多準則決策模型,決策表,基因演算法,貪婪演算法,求解空間 , Multi-criteria decision making model, Decision table, Genetic algorithm (GA), Greedy algorithm, Solution space]

多準則決策表格的摘要化方法 1040801~1050731 [多準則決策模型,決策表,基因演算法,貪婪演算法,求解空間 , Multi-criteria decision making model, Decision table, Genetic algorithm (GA), Greedy algorithm, Solution space]

期刊著作

A3BRec: A Novel Association-Integration Sequential Basket Recommendation IEEE Transactions on Knowledge and Data Engineering, 38, 2, 800-813, 2026-01-01 [ Association rule,deep learning,recommendation system,transformer ]

Using large multimodal models to predict outfit compatibility Decision Support Systems, 194, 2025-07-01 [ Large language models,Large multi-modal models,Outfit compatibility,Outfit recommendation ]

PIFTA4Rec: leveraging personalized item frequency and temporal attention for enhanced next-basket recommendation Journal of Supercomputing, 81, 8, 2025-06-01 [ Deep learning,Item2Vec,K nearest neighbor,Next-basket recommendation,Personalized item frequency ]

G-TransRec: A Transformer-Based Next-Item Recommendation With Time Prediction IEEE Transactions on Computational Social Systems, 11, 3, 4175-4188, 2024-06-01 [ Deep learning,item and time prediction,neural network,sequential recommendation,transformer ]

Using personalized next session to improve session-based recommender systems Journal of Supercomputing, 80, 6, 7369-7398, 2024-04-01 [ Deep learning,Global information,Neural network,Personalized recommendation,Session embedding,Session-based recommendation ]

A novel virtual-communicated evolution learning recommendation Industrial Management and Data Systems, 124, 1, 416-441, 2024-01-02 [ Deep learning,Long short-term memory,Matrix factorization,Recommendation system ]

A deep multi-embedding model for mobile application recommendation Decision Support Systems, 173, 2023-10-01 [ Deep learning,Matrix factorization,Multi-embedding,Neural networks,Recommender system ]

A cross-platform recommendation system from Facebook to Instagram Electronic Library, 41, 2-3, 264-285, 2023-05-24 [ Cross-platform recommendation system,Facebook,Instagram,Social media ]

對「漫談學術生涯：機會、創新與滿意度」回應 Response to ＂On Academic Life: Opportunities, Innovation, and Satisfaction＂ 管理學報, 39, 3, 289-292, 2022-09-01 [ 機會,創新 ]

Aspect-based sentiment analysis with component focusing multi-head co-attention networks Neurocomputing, 489, 9-17, 2022-06-07 [ BERT,Deep learning,Neural network,Sentiment analysis ]

An ensemble model for link prediction based on graph embedding Decision Support Systems, 157, 2022-06-01 [ Ensemble learning,Graph embedding,Link prediction ]

MK-Means: Detecting evolutionary communities in dynamic networks Expert Systems with Applications, 176, 2021-08-15 [ Clustering,Evolutionary clustering,K-Means,Social community ]

Noise-free attribute-oriented induction Information Sciences, 568, 333-349, 2021-08-01 [ Attribute-Oriented Induction,Concept Hierarchy,Data mining,Noise ]

Predicting ewom’s influence on purchase intention based on helpfulness, credibility, information quality and professionalism Sustainability, 13, 13, 2021-07-01 [ Credibility,Electronic word-of-mouth (eWOM),Helpfulness,Information quality,Professionalism,Purchase intention ]

A movie recommendation method based on users' positive and negative profiles Information Processing and Management, 58, 3, 2021-05-01 [ Collaborative filtering,Hybrid recommendation,Recommendation,User profile ]

A template approach for summarizing restaurant reviews IEEE Access, 9, 115548-115562, 2021-01-01 [ Restaurant reviews,sentiment analysis,summarization,template,TextRank ]

Building a training dataset for classification under a cost limitation Electronic Library, 39, 1, 77-96, 2021-01-01 [ Big data,Classification,Data mining,Text mining ]

Summarization of information systems based on rough set theory Journal of Intelligent and Fuzzy Systems, 40, 1, 1001-1015, 2021-01-01 [ Attribute reduction,Information system,Reduct,Rough set,Summarization ]

Mining specific and representative information by the attribute-oriented induction method Expert Systems, 2020-01-01 [ attribute-oriented induction,concept hierarchy,cost,data mining,noise ]

Early prediction of the future popularity of uploaded videos Expert Systems with Applications, 133, 59-74, 2019-11-01 [ Data mining , Popularity prediction , YouTube ]

Cost-sensitive decision tree with multiple resource constraints Applied Intelligence, 49, 10, 3765-3782, 2019-10-01 [ Cost-sensitive learning , Data mining , Decision tree , Machine Learning ]

An innovative citation recommendation model for draft papers with varying degrees of information completeness Data Technologies and Applications, 53, 4, 562-576, 2019-09-03 [ Citation , Draft paper , Incompleteness , Recommendation system , Text mining , WordNet ]

A two-phase sentiment analysis approach for judgement prediction Journal of Information Science, 44, 5, 594-607, 2018-10-01 [ Criminal precedent , judgement classification , sentiment analysis , support vector machines (SVM) , text mining ]

Emotion classification of YouTube videos Decision Support Systems, 101, 40-50, 2017-09-01 [ Data mining , Machine learning , Sentiments analysis , YouTube ]

A two-stage clustering algorithm for the two-attribute-set problem Advanced Science Letters, 23, 5, 4258-4262, 2017-05-01 [ Cluster analysis , Clustering , Data mining ]

A two-attributes-set spatial clustering algorithm for geography data Advanced Science Letters, 23, 5, 3843-3848, 2017-05-01 [ Cluster analysis , Data mining , Spatial clustering ]

Opinion mining from online hotel reviews – A text summarization approach Information Processing and Management, 53, 2, 436-449, 2017-03-01 [ k-medoids , Multi-text summarization , Online hotel review , Sentence clustering , Sentiment analysis ]

Identifying conflict patterns to reach a consensus - A novel group decision approach European Journal of Operational Research, 254, 2, 622-631, 2016-10-16 [ Conflict patterns , Data mining , Decision-making , Group decision-making , Maximum consensus sequence ]

Decision tree induction with a constrained number of leaf nodes Applied Intelligence, 45, 3, 673-685, 2016-10-01 [ Classification , Constraint tree , Data mining , Decision tree ]

A novel recommendation model with Google similarity Decision Support Systems, 89, 17-27, 2016-09-01 [ Collaborative filtering , Data mining , Normalized Google distance , Recommender system ]

Time-constrained cost-sensitive decision tree induction Information Sciences, 354, 140-152, 2016-08-01 [ Classification , Cost-sensitive learning , Data mining , Decision analysis , Decision tree ]

A novel approach to rate and summarize online reviews according to user-specified aspects Journal of Electronic Commerce Research, 17, 2, 132-152, 2016-05-01 [ K-means , Normalized google distance , Online reviews , Opinion mining , Sentiment analysis ]

A novel summarization technique for the support of resolving multi-criteria decision making problems Decision Support Systems, 79, 109-124, 2015-11-01 [ Decision table , Genetic algorithm , Multi-criteria decision making , Summarization ]

An annotation approach to contextual advertising for online ADS Journal of Electronic Commerce Research, 16, 2, 123-137, 2015-01-01 [ Annotation , Contextual advertising , Online advertisements , Recommendation , Tag ]

Predicting associated statutes for legal problems Information Processing and Management, 51, 1, 194-211, 2015-01-01 [ (NGD) , (SVM) , Apriori algorithm , Criminal judgment , Distance , Google , Normalized , Statute , Support vector machines , Text mining ]

Predicting the influence of users' posted information for eWOM advertising in social networks Electronic Commerce Research and Applications, 13, 6, 431-439, 2014-01-01 [ Data mining , Electronic word-of-mouth (eWOM) , Influence , Sentiment analysis , Social network ]

Community detection based on social interactions in a social network Journal of the Association for Information Science and Technology, 65, 3, 539-550, 2014-01-01

Cross-language patent matching via an international patent classification-based concept bridge Journal of Information Science, 39, 6, 737-753, 2013-12-01 [ cross-language patent matching , latent semantic indexing , patent mining ]

A new approach to the group ranking problem: Finding consensus ordered segments from users' preference data Decision Sciences, 44, 6, 1091-1119, 2013-12-01 [ Artificial Intelligence , Cluster Analysis , Collaborative Decision Models , Group Decision Support , Group/Team Decision Making ]

A novel decision-tree method for structured continuous-label classification IEEE Transactions on Cybernetics, 43, 6, 1734-1746, 2013-12-01 [ Classification algorithms , Data mining , Decision trees (DTs) ]

A text mining approach to assist the general public in the retrieval of legal documents Journal of the American Society for Information Science and Technology, 64, 2, 280-290, 2013-02-01 [ information retrieval , text mining ]

Conjecturable knowledge discovery: A fuzzy clustering approach Fuzzy Sets and Systems, 221, 1-23, 2013-01-22 [ Classification , Conjecturable rules , Data mining , Fuzzy clustering ]

Mining consensus preference graphs from users' ranking data Decision Support Systems, 54, 2, 1055-1064, 2013-01-01 [ Data mining , Decision making , Group decision making , Maximum consensus sequence , Preference graph ]

A three-phase method for patent classification Information Processing and Management, 48, 6, 1017-1030, 2012-11-01 [ IPC taxonomy , K nearest neighbors (KNN) , K-means , Patent classification , Support vector machines (SVM) , Vector space model (VSM) ]

Vector space model for patent documents with hierarchical class labels Journal of Information Science, 38, 3, 222-233, 2012-06-01 [ document classification , feature selection , hierarchical class label , vector space model (VSM) ]

From data to global generalized knowledge Decision Support Systems, 52, 2, 295-307, 2012-01-01 [ Attribute-oriented induction , Data mining , Generalized knowledge , Multiple-level mining ]

An evolutionary PageRank approach for journal ranking with expert judgements Journal of Information Science, 37, 3, 254-272, 2011-06-01 [ citation-based approach , experts' survey method , journal ranking , PageRank , Particle Swarm Optimization ]

An IPC-based vector space model for patent retrieval Information Processing and Management, 47, 3, 309-322, 2011-05-01 [ Patent mining , Patent retrieval , Vector space model (VSM) ]

考慮關聯性、新奇性、購物籃大小的循序推薦
1150801~1160731

考慮關聯性、新奇性、購物籃大小的循序推薦
1140801~1150731

以深度學習為基的推薦系統
1140801~1150731

考慮關聯性、新奇性、購物籃大小的循序推薦
1130801~1140731

以深度學習為基的推薦系統
1130801~1140731

以深度學習為基的推薦系統
1120801~1130731

三個推薦系統的擴增與改進
1120801~1130731
[推薦,協同推薦,深度學習模型,時間衰殘,跨平台推薦 , Recommendation,collaborative recommendation,deep learning model,time decay,cross-platform recommendation]

使用多種圖編碼進行鏈結預測
1110801~1120731
[鏈結預測,網絡嵌入,集成學習,深度神經網路 , Link prediction,Ensemble　learning,Graph　 embedding,Deep Neural Network]

三個推薦系統的擴增與改進
1110801~1120731
[推薦,協同推薦,深度學習模型,時間衰殘,跨平台推薦 , Recommendation,collaborative recommendation,deep learning model,time decay,cross-platform recommendation]

一個面向等級的情緒分析深度學習方法
1100801~1110731
[情感分析、深度學習、文字嵌入、自我注意力、構件聚焦 , Sentiment analysis,deep learning,word embedding,self-attention,component focusing]

三個推薦系統的擴增與改進
1100801~1110731
[推薦,協同推薦,深度學習模型,時間衰殘,跨平台推薦 , Recommendation,collaborative recommendation,deep learning model,time decay,cross-platform recommendation]

在成本/資源限制下選擇資料進行標註
1090801~1100731
[分類,非監督式樣本選取,成本,資源,分類器 , Classification,Unsupervised instance selection,Cost,Resource,Classifiers]

在成本/資源限制下選擇資料進行標註
1080801~1090731
[分類,非監督式樣本選取,成本,資源,分類器 , Classification,Unsupervised instance selection,Cost,Resource,Classifiers]

具最小歸納成本之屬性導向歸納法
1070801~1080731
[屬性導向歸納法,分群演算法,基因演算法,貪婪演算法,一般化表格 , Attribute-Oriented Induction,Clustering,Genetic algorithm (GA),Greedy Algorithm, Generalized Table]

在成本/資源限制下選擇資料進行標註
1070801~1080731
[分類,非監督式樣本選取,成本,資源,分類器 , Classification,Unsupervised instance selection,Cost,Resource,Classifiers]

具最小歸納成本之屬性導向歸納法
1060801~1070731
[屬性導向歸納法,分群演算法,基因演算法,貪婪演算法,一般化表格 , Attribute-Oriented Induction,Clustering,Genetic algorithm (GA),Greedy Algorithm, Generalized Table]

多準則決策表格的摘要化方法
1060801~1070731
[多準則決策模型,決策表,基因演算法,貪婪演算法,求解空間 , Multi-criteria decision making model, Decision table, Genetic algorithm (GA), Greedy algorithm, Solution space]

具最小歸納成本之屬性導向歸納法
1050801~1060731
[屬性導向歸納法,分群演算法,基因演算法,貪婪演算法,一般化表格 , Attribute-Oriented Induction,Clustering,Genetic algorithm (GA),Greedy Algorithm, Generalized Table]

多準則決策表格的摘要化方法
1050801~1060731
[多準則決策模型,決策表,基因演算法,貪婪演算法,求解空間 , Multi-criteria decision making model, Decision table, Genetic algorithm (GA), Greedy algorithm, Solution space]

多準則決策表格的摘要化方法
1040801~1050731
[多準則決策模型,決策表,基因演算法,貪婪演算法,求解空間 , Multi-criteria decision making model, Decision table, Genetic algorithm (GA), Greedy algorithm, Solution space]

A3BRec: A Novel Association-Integration Sequential Basket Recommendation
IEEE Transactions on Knowledge and Data Engineering, 38, 2, 800-813, 2026-01-01
[ Association rule,deep learning,recommendation system,transformer ]

Using large multimodal models to predict outfit compatibility
Decision Support Systems, 194, 2025-07-01
[ Large language models,Large multi-modal models,Outfit compatibility,Outfit recommendation ]

PIFTA4Rec: leveraging personalized item frequency and temporal attention for enhanced next-basket recommendation
Journal of Supercomputing, 81, 8, 2025-06-01
[ Deep learning,Item2Vec,K nearest neighbor,Next-basket recommendation,Personalized item frequency ]

G-TransRec: A Transformer-Based Next-Item Recommendation With Time Prediction
IEEE Transactions on Computational Social Systems, 11, 3, 4175-4188, 2024-06-01
[ Deep learning,item and time prediction,neural network,sequential recommendation,transformer ]

Using personalized next session to improve session-based recommender systems
Journal of Supercomputing, 80, 6, 7369-7398, 2024-04-01
[ Deep learning,Global information,Neural network,Personalized recommendation,Session embedding,Session-based recommendation ]

A novel virtual-communicated evolution learning recommendation
Industrial Management and Data Systems, 124, 1, 416-441, 2024-01-02
[ Deep learning,Long short-term memory,Matrix factorization,Recommendation system ]

A deep multi-embedding model for mobile application recommendation
Decision Support Systems, 173, 2023-10-01
[ Deep learning,Matrix factorization,Multi-embedding,Neural networks,Recommender system ]

A cross-platform recommendation system from Facebook to Instagram
Electronic Library, 41, 2-3, 264-285, 2023-05-24
[ Cross-platform recommendation system,Facebook,Instagram,Social media ]

對「漫談學術生涯：機會、創新與滿意度」回應 Response to ＂On Academic Life: Opportunities, Innovation, and Satisfaction＂
管理學報, 39, 3, 289-292, 2022-09-01
[ 機會,創新 ]

Aspect-based sentiment analysis with component focusing multi-head co-attention networks
Neurocomputing, 489, 9-17, 2022-06-07
[ BERT,Deep learning,Neural network,Sentiment analysis ]

An ensemble model for link prediction based on graph embedding
Decision Support Systems, 157, 2022-06-01
[ Ensemble learning,Graph embedding,Link prediction ]

MK-Means: Detecting evolutionary communities in dynamic networks
Expert Systems with Applications, 176, 2021-08-15
[ Clustering,Evolutionary clustering,K-Means,Social community ]

Noise-free attribute-oriented induction
Information Sciences, 568, 333-349, 2021-08-01
[ Attribute-Oriented Induction,Concept Hierarchy,Data mining,Noise ]

Predicting ewom’s influence on purchase intention based on helpfulness, credibility, information quality and professionalism
Sustainability, 13, 13, 2021-07-01
[ Credibility,Electronic word-of-mouth (eWOM),Helpfulness,Information quality,Professionalism,Purchase intention ]

A movie recommendation method based on users' positive and negative profiles
Information Processing and Management, 58, 3, 2021-05-01
[ Collaborative filtering,Hybrid recommendation,Recommendation,User profile ]

A template approach for summarizing restaurant reviews
IEEE Access, 9, 115548-115562, 2021-01-01
[ Restaurant reviews,sentiment analysis,summarization,template,TextRank ]

Building a training dataset for classification under a cost limitation
Electronic Library, 39, 1, 77-96, 2021-01-01
[ Big data,Classification,Data mining,Text mining ]

Summarization of information systems based on rough set theory
Journal of Intelligent and Fuzzy Systems, 40, 1, 1001-1015, 2021-01-01
[ Attribute reduction,Information system,Reduct,Rough set,Summarization ]

Mining specific and representative information by the attribute-oriented induction method
Expert Systems, 2020-01-01
[ attribute-oriented induction,concept hierarchy,cost,data mining,noise ]

Early prediction of the future popularity of uploaded videos
Expert Systems with Applications, 133, 59-74, 2019-11-01
[ Data mining , Popularity prediction , YouTube ]

Cost-sensitive decision tree with multiple resource constraints
Applied Intelligence, 49, 10, 3765-3782, 2019-10-01
[ Cost-sensitive learning , Data mining , Decision tree , Machine Learning ]

An innovative citation recommendation model for draft papers with varying degrees of information completeness
Data Technologies and Applications, 53, 4, 562-576, 2019-09-03
[ Citation , Draft paper , Incompleteness , Recommendation system , Text mining , WordNet ]

A two-phase sentiment analysis approach for judgement prediction
Journal of Information Science, 44, 5, 594-607, 2018-10-01
[ Criminal precedent , judgement classification , sentiment analysis , support vector machines (SVM) , text mining ]

Emotion classification of YouTube videos
Decision Support Systems, 101, 40-50, 2017-09-01
[ Data mining , Machine learning , Sentiments analysis , YouTube ]

A two-stage clustering algorithm for the two-attribute-set problem
Advanced Science Letters, 23, 5, 4258-4262, 2017-05-01
[ Cluster analysis , Clustering , Data mining ]

A two-attributes-set spatial clustering algorithm for geography data
Advanced Science Letters, 23, 5, 3843-3848, 2017-05-01
[ Cluster analysis , Data mining , Spatial clustering ]

Opinion mining from online hotel reviews – A text summarization approach
Information Processing and Management, 53, 2, 436-449, 2017-03-01
[ k-medoids , Multi-text summarization , Online hotel review , Sentence clustering , Sentiment analysis ]

Identifying conflict patterns to reach a consensus - A novel group decision approach
European Journal of Operational Research, 254, 2, 622-631, 2016-10-16
[ Conflict patterns , Data mining , Decision-making , Group decision-making , Maximum consensus sequence ]

Decision tree induction with a constrained number of leaf nodes
Applied Intelligence, 45, 3, 673-685, 2016-10-01
[ Classification , Constraint tree , Data mining , Decision tree ]

A novel recommendation model with Google similarity
Decision Support Systems, 89, 17-27, 2016-09-01
[ Collaborative filtering , Data mining , Normalized Google distance , Recommender system ]

Time-constrained cost-sensitive decision tree induction
Information Sciences, 354, 140-152, 2016-08-01
[ Classification , Cost-sensitive learning , Data mining , Decision analysis , Decision tree ]

A novel approach to rate and summarize online reviews according to user-specified aspects
Journal of Electronic Commerce Research, 17, 2, 132-152, 2016-05-01
[ K-means , Normalized google distance , Online reviews , Opinion mining , Sentiment analysis ]

A novel summarization technique for the support of resolving multi-criteria decision making problems
Decision Support Systems, 79, 109-124, 2015-11-01
[ Decision table , Genetic algorithm , Multi-criteria decision making , Summarization ]

An annotation approach to contextual advertising for online ADS
Journal of Electronic Commerce Research, 16, 2, 123-137, 2015-01-01
[ Annotation , Contextual advertising , Online advertisements , Recommendation , Tag ]

Predicting associated statutes for legal problems
Information Processing and Management, 51, 1, 194-211, 2015-01-01
[ (NGD) , (SVM) , Apriori algorithm , Criminal judgment , Distance , Google , Normalized , Statute , Support vector machines , Text mining ]

Predicting the influence of users' posted information for eWOM advertising in social networks
Electronic Commerce Research and Applications, 13, 6, 431-439, 2014-01-01
[ Data mining , Electronic word-of-mouth (eWOM) , Influence , Sentiment analysis , Social network ]

Community detection based on social interactions in a social network
Journal of the Association for Information Science and Technology, 65, 3, 539-550, 2014-01-01

Cross-language patent matching via an international patent classification-based concept bridge
Journal of Information Science, 39, 6, 737-753, 2013-12-01
[ cross-language patent matching , latent semantic indexing , patent mining ]

A new approach to the group ranking problem: Finding consensus ordered segments from users' preference data
Decision Sciences, 44, 6, 1091-1119, 2013-12-01
[ Artificial Intelligence , Cluster Analysis , Collaborative Decision Models , Group Decision Support , Group/Team Decision Making ]

A novel decision-tree method for structured continuous-label classification
IEEE Transactions on Cybernetics, 43, 6, 1734-1746, 2013-12-01
[ Classification algorithms , Data mining , Decision trees (DTs) ]

A text mining approach to assist the general public in the retrieval of legal documents
Journal of the American Society for Information Science and Technology, 64, 2, 280-290, 2013-02-01
[ information retrieval , text mining ]

Conjecturable knowledge discovery: A fuzzy clustering approach
Fuzzy Sets and Systems, 221, 1-23, 2013-01-22
[ Classification , Conjecturable rules , Data mining , Fuzzy clustering ]

Mining consensus preference graphs from users' ranking data
Decision Support Systems, 54, 2, 1055-1064, 2013-01-01
[ Data mining , Decision making , Group decision making , Maximum consensus sequence , Preference graph ]

A three-phase method for patent classification
Information Processing and Management, 48, 6, 1017-1030, 2012-11-01
[ IPC taxonomy , K nearest neighbors (KNN) , K-means , Patent classification , Support vector machines (SVM) , Vector space model (VSM) ]

Vector space model for patent documents with hierarchical class labels
Journal of Information Science, 38, 3, 222-233, 2012-06-01
[ document classification , feature selection , hierarchical class label , vector space model (VSM) ]

From data to global generalized knowledge
Decision Support Systems, 52, 2, 295-307, 2012-01-01
[ Attribute-oriented induction , Data mining , Generalized knowledge , Multiple-level mining ]

An evolutionary PageRank approach for journal ranking with expert judgements
Journal of Information Science, 37, 3, 254-272, 2011-06-01
[ citation-based approach , experts' survey method , journal ranking , PageRank , Particle Swarm Optimization ]

An IPC-based vector space model for patent retrieval
Information Processing and Management, 47, 3, 309-322, 2011-05-01
[ Patent mining , Patent retrieval , Vector space model (VSM) ]

Mining negative generalized knowledge from relational databases
Knowledge-Based Systems, 24, 1, 134-145, 2011-02-01
[ Attribute-oriented induction , Data mining , Generalized knowledge , Multiple-level mining , Negative pattern ]

Discovering multi-label temporal patterns in sequence databases
Information Sciences, 181, 3, 398-418, 2011-02-01
[ Interval-based event sequence , Point-based event sequence , Sequential patterns , Temporal patterns ]

Mining associative classification rules with stock trading data-A GA-based method
Knowledge-Based Systems, 23, 6, 605-614, 2010-08-01
[ Associative classification rules , Data mining , Genetic algorithm , Numerical data ]

Mining fuzzy association rules from uncertain data
Knowledge and Information Systems, 23, 2, 129-152, 2010-05-01
[ Data mining , Fuzzy association rules , Fuzzy statistics and data analysis , Learning , Uncertain data ]

An approach to group ranking decisions in a dynamic environment
Decision Support Systems, 48, 4, 622-634, 2010-03-01
[ Data mining , Group decision making , Group ranking , Maximum consensus sequence ]

Gene clustering by using query-based self-organizing maps
Expert Systems with Applications, 37, 9, 6689-6694, 2010-01-01
[ Bioinformatics , Data clustering , Data mining , Gene expression , Microarray analysis , Neural networks , Query-based learning , Self-organizing maps ]

Mining sequential patterns in the B2B environment
Journal of Information Science, 35, 6, 677-694, 2009-12-01
[ Business-to-business , Data mining , Sequential pattern ]

Discovering hybrid temporal patterns from sequences consisting of point- and interval-based events
Data and Knowledge Engineering, 68, 11, 1309-1330, 2009-11-01
[ Data mining , Hybrid event sequences , Hybrid temporal pattern , Sequential pattern , Temporal pattern ]

A dynamic discretization approach for constructing decision trees with a continuous label
IEEE Transactions on Knowledge and Data Engineering, 21, 11, 1505-1514, 2009-11-01
[ Classification. , Data mining , Decision trees ]

Discovering recency, frequency, and monetary (RFM) sequential patterns from customers' purchasing data
Electronic Commerce Research and Applications, 8, 5, 241-251, 2009-10-01
[ Constraint-based mining , RFM , Segmentation , Sequential pattern ]

Mining maximum consensus sequences from group ranking data
European Journal of Operational Research, 198, 1, 241-251, 2009-10-01
[ Data mining , Decision making , Group decision making , Maximum consensus sequence ]

On mining multi-time-interval sequential patterns
Data and Knowledge Engineering, 68, 10, 1112-1127, 2009-10-01
[ Data mining , Knowledge discovery , Multi-time-interval , Sequential pattern , Time-interval ]