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IEEE Transactions on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, 08/2017, Volume 39, Issue 8, pp. 1633 - 1647
Journal Article
IEEE Transactions on Knowledge and Data Engineering, ISSN 1041-4347, 03/2014, Volume 26, Issue 3, pp. 766 - 779
Journal Article
ACM Computing Surveys (CSUR), ISSN 0360-0300, 07/2014, Volume 47, Issue 1, pp. 1 - 45
Over the past two decades, a large amount of research effort has been devoted to developing algorithms that generate recommendations. The resulting research... 
collaborative filtering | recommender systems | Algorithms | challenges | social networks | survey | applications | Survey | Applications | Collaborative filtering | Challenges | Social networks | Recommender systems | INFORMATION | ALGORITHM | MODEL | Design | DISTRIBUTIONS | SOCIAL BOOKMARKING | COMPUTER SCIENCE, THEORY & METHODS | Performance | TRUST | Information storage and retrieval | Surveys
Journal Article
ACM Transactions on Information Systems (TOIS), ISSN 1046-8188, 01/2004, Volume 22, Issue 1, pp. 5 - 53
Recommender systems have been evaluated in many, often incomparable, ways. In this article, we review the key decisions in evaluating collaborative filtering... 
evaluation | recommender systems | metrics | Collaborative filtering | Evaluation | Metrics | Recommender systems | collaborative filtering | RETRIEVAL EFFECTIVENESS | performance | experimentation | COMPUTER SCIENCE, INFORMATION SYSTEMS | measurement | Metric system | Models
Journal Article
Neurocomputing, ISSN 0925-2312, 10/2018, Volume 311, pp. 88 - 98
Neighborhood-based collaborative filtering is a method of high significance among recommender systems, with advantages of simplicity and justifiability.... 
Attention model | Deep learning | Collaborative filtering | Recommender system | RECOMMENDER | NETWORKS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
Information Sciences, ISSN 0020-0255, 2012, Volume 185, Issue 1, pp. 1 - 17
It seems reasonable to think that there may be some items and some users in a recommender system that could be highly significant in making recommendations.... 
Items | Collaborative filtering | Significances | Recommender systems | ALGORITHM | COMPUTER SCIENCE, INFORMATION SYSTEMS | OF-THE-ART | TRUST | HYBRID | Apples | Filtering | Filtration | Similarity | Television | Mathematical analysis | News | Ratings
Journal Article
ACM Computing Surveys (CSUR), ISSN 0360-0300, 11/2016, Volume 49, Issue 2, pp. 1 - 41
Collaborative filtering is among the most preferred techniques when implementing recommender systems. Recently, great interest has turned toward parallel and... 
Collaborative filtering | recommender systems | Recommender systems | AWARE RECOMMENDER SYSTEMS | Algorithms | Documentation | CLASSIFICATION | COMPUTER SCIENCE, THEORY & METHODS | MATRIX FACTORIZATION | OF-THE-ART | Surveys | Computer programming | Internet service providers
Journal Article
Knowledge-Based Systems, ISSN 0950-7051, 07/2018, Volume 152, pp. 94 - 99
Recommender Systems (RS) provide a relevant tool to mitigate the information overload problem. A large number of researchers have published hundreds of papers... 
Java | Collaborative filtering | Recommender systems | Framework | MATRIX FACTORIZATION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
Computer Communications, ISSN 0140-3664, 03/2014, Volume 41, pp. 1 - 10
Recommendation plays an increasingly important role in our daily lives. Recommender systems automatically suggest to a user items that might be of interest to... 
Collaborative filtering | Social network | Recommender system | COMPUTER SCIENCE, INFORMATION SYSTEMS | NETWORKS | TELECOMMUNICATIONS | SIMILARITY | TRUST | ENGINEERING, ELECTRICAL & ELECTRONIC
Journal Article
26th International World Wide Web Conference, WWW 2017, 2017, pp. 173 - 182
Conference Proceeding
Proceedings of the 18th international conference on world wide web, 04/2009, pp. 681 - 690
Users of social networking services can connect with each other by forming communities for online interaction. Yet as the number of communities hosted by such... 
latent topic models | collaborative filtering | recommender systems | data mining | association rule mining | Association rule mining | Collaborative filtering | Latent topic models | Data mining | Recommender systems
Conference Proceeding
IEEE Transactions on Services Computing, ISSN 1939-1374, 04/2011, Volume 4, Issue 2, pp. 140 - 152
With increasing presence and adoption of Web services on the World Wide Web, Quality-of-Service (QoS) is becoming important for describing nonfunctional... 
Training | collaborative filtering | Accuracy | service recommendation | Web services | QoS | Collaboration | Quality of service | Web service | service selection | Computational complexity | Equations | Studies | Internet service providers | Conduction | Algorithms | Filtering | Filtration | Java (programming language) | Collection | Internet
Journal Article
Expert Systems With Applications, ISSN 0957-4174, 04/2016, Volume 48, pp. 100 - 110
Journal Article
ACM Transactions on the Web (TWEB), ISSN 1559-1131, 02/2011, Volume 5, Issue 1, pp. 1 - 33
The technique of collaborative filtering is especially successful in generating personalized recommendations. More than a decade of research has resulted in... 
Collaborative filtering | recommender systems | Recommender systems | COMPUTER SCIENCE, SOFTWARE ENGINEERING | COMPUTER SCIENCE, INFORMATION SYSTEMS | Algorithms | Performance
Journal Article
Future Generation Computer Systems, ISSN 0167-739X, 04/2019, Volume 93, pp. 1046 - 1054
It is the era of information explosion and overload. The recommender systems can help people quickly get the expected information when facing the enormous data... 
Collaborative Filtering | Category preferred ratio | Data mining | Recommender system | COMPUTER SCIENCE, THEORY & METHODS | Computer science | Algorithms
Journal Article
ACM Transactions on Information Systems (TOIS), ISSN 1046-8188, 01/2004, Volume 22, Issue 1, pp. 89 - 115
Collaborative filtering aims at learning predictive models of user preferences, interests or behavior from community data, that is, a database of available... 
Collaborative filtering | Latent semantic analysis | Recommender systems | Machine learning | Mixture models | collaborative filtering | recommender systems | ALGORITHM | COMPUTER SCIENCE, INFORMATION SYSTEMS | machine learning | mixture models | latent semantic analysis | Semantics | Models | Filtration
Journal Article
Expert Systems With Applications, ISSN 0957-4174, 2011, Volume 38, Issue 12, pp. 14609 - 14623
► Framework to evaluate the quality results of any collaborative filtering based recommender system. ► Provides 4 graphs: quality of the predictions, the... 
Collaborative filtering | Similarity measures | Quality | Trust | Recommender systems | Framework | Novelty | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Graphs | Filtration | Filtering | Consolidation | Mathematical analysis | Expert systems
Journal Article
Artificial Intelligence, ISSN 0004-3702, 04/2013, Volume 197, pp. 39 - 55
A major challenge for collaborative filtering (CF) techniques in recommender systems is the data sparsity that is caused by missing and noisy ratings. This... 
Collaborative filtering | Transfer learning | Missing ratings | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
Information Sciences, ISSN 0020-0255, 12/2019, Volume 505, pp. 535 - 548
Collaborative filtering (CF) approaches are widely applied in recommender systems. Traditional CF approaches have high costs to train the models and cannot... 
Dynamic regularization | Collaborative filtering | Neighborhood factor | Online collaborative filtering | RECOMMENDER SYSTEMS | COMPUTER SCIENCE, INFORMATION SYSTEMS
Journal Article