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Knowledge-Based Systems, ISSN 0950-7051, 02/2014, Volume 57, pp. 57 - 68
Providing high quality recommendations is important for e-commerce systems to assist users in making effective selection decisions from a plethora of choices.... 
Trusted neighbors | Collaborative filtering | Data sparsity | Recommender systems | Cold start | INFORMATION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Cold starts | Filtration | Filtering | Similarity | Confidence | Merging | Knowledge base | Ratings
Journal Article
Knowledge-Based Systems, ISSN 0950-7051, 01/2015, Volume 74, pp. 14 - 27
Although demonstrated to be efficient and scalable to large-scale data sets, clustering-based recommender systems suffer from relatively low accuracy and... 
Collaborative filtering | Similarity | Trust | Recommender systems | Cold start | Multiview clustering | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Accuracy | Data sets | Clusters | Regression | Mathematical models | Clustering | Ratings
Journal Article
Decision Support Systems, ISSN 0167-9236, 03/2015, Volume 71, pp. 37 - 47
Many trust-aware recommender systems have explored the value of explicit trust, which is specified by users with binary values and simply treated as a concept... 
Distrust | Trust | Rating behavior | Recommender systems | Multi-facet | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | COMPUTER SCIENCE, INFORMATION SYSTEMS | MODEL | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Decision support systems | Data sets | Historic | Regression | Mathematical models | Joints | Logistics | Integrity
Journal Article
Energy Procedia, ISSN 1876-6102, 02/2019, Volume 158, pp. 1086 - 1092
The operation mode of "fixing heat based on power" in the heating season of "Three North" areas in China is one of the essential reasons for the phenomenon of... 
the law of marginal benefits | capacity optimization | distributed heat storage station | phase-change heat storage station
Journal Article
Journal Article
Proceedings of the 29th Annual ACM Symposium on applied computing, 03/2014, pp. 248 - 253
Trust has been extensively studied and its effectiveness demonstrated in recommender systems. Due to the lack of explicit trust information in most systems,... 
recommender systems | trust metrics | ratings | similarity | Similarity | Trust metrics | Recommender systems | Ratings
Conference Proceeding
IEEE Transactions on Knowledge and Data Engineering, ISSN 1041-4347, 07/2016, Volume 28, Issue 7, pp. 1607 - 1620
Journal Article
Electronic Commerce Research and Applications, ISSN 1567-4223, 11/2014, Volume 13, Issue 6, pp. 440 - 455
User ratings are the essence of recommender systems in e-commerce. Lack of motivation to provide ratings and eligibility to rate generally only after purchase... 
Rating confidence | Prior ratings | Data sparsity | Similarity measure | Recommender systems | Cold start | QUALITY | PRICE | INFORMATION | BEHAVIOR | COMPUTER SCIENCE, INFORMATION SYSTEMS | BUSINESS | MODEL | BRAND | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | ALLEVIATE | EXPERIENCE | TRUST | PERCEPTIONS | Electronic commerce | Evaluation | Analysis
Journal Article
Knowledge-Based Systems, ISSN 0950-7051, 04/2017, Volume 122, pp. 17 - 25
Trust-aware recommender systems have attracted much attention recently due to the prevalence of social networks. However, most existing trust-based approaches... 
Matrix factorization | Social trust | Trust influence | Recommender systems | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Social networks | Analysis | Incorporation
Journal Article
Proceedings of the National Conference on Artificial Intelligence, 06/2015, Volume 1, pp. 123 - 129
Conference Proceeding
Information Sciences, ISSN 0020-0255, 04/2018, Volume 436-437, pp. 56 - 73
•We propose a time-aware matrix factorization model that considers both periodic and continual temporal effects.•We conduct analysis to confirm the two types... 
Continual effect | Co-factorization model | Rating timestamps | Periodic effect | Recommender systems | Temporal model | COMPUTER SCIENCE, INFORMATION SYSTEMS
Journal Article
Knowledge-Based Systems, ISSN 0950-7051, 12/2017, Volume 138, pp. 202 - 207
Data sparsity is a well-recognized issue for Top-N item recommendation, which depends on user preference gathered from their historical behaviors (i.e.,... 
Implicit feedback | Data sparsity | Recommender systems | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
Information Sciences, ISSN 0020-0255, 07/2018, Volume 453, pp. 80 - 98
Personalized recommendation for online service systems aims to predict potential demand by analysing user preference. User preference can be inferred from... 
Heterogeneous implicit feedback | Co-occurrence | Recommendation | Personalized ranking | COMPUTER SCIENCE, INFORMATION SYSTEMS | FACTORIZATION
Journal Article
Open Civil Engineering Journal, ISSN 1874-1495, 2015, Volume 9, Issue 1, pp. 426 - 434
Most of the laboratory tests investigated the flexural performance of un-preloaded or undamaged RC beams strengthened with CFRP composites. However, in... 
Preload level | CFRP-strengthened | RC beam | Flexural load-carrying capacity
Journal Article
ACM Transactions on the Web (TWEB), ISSN 1559-1131, 05/2016, Volume 10, Issue 2, pp. 1 - 30
User-based collaborative filtering , a widely used nearest neighbour-based recommendation technique, predicts an item's rating by aggregating its ratings from... 
similarity measure | Bayesian similarity | Recommender systems | Dirichlet distribution | Similarity measure | COMPUTER SCIENCE, SOFTWARE ENGINEERING | Algorithms | COMPUTER SCIENCE, INFORMATION SYSTEMS | Performance | Correlation | Similarity | Mathematical analysis | Dirichlet problem | Vectors (mathematics) | Bayesian analysis | Ratings
Journal Article
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN 0302-9743, 2018, Volume 11164, pp. 744 - 754
Conference Proceeding
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