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Using Implicit Preference Relations to Improve Recommender Systems

, and . Journal on Data Semantics, 6 (1): 15--30 (2017)
DOI: 10.1007/s13740-016-0061-8

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Escr Lscr description logics with aggregation of user preference concepts.. EJC, volume 154 of Frontiers in Artificial Intelligence and Applications, page 154-165. IOS Press, (2006)Multi-Criterion Search from the Semantic Point of View - (Comparing TIL and Description Logic)., and . EJC, volume 166 of Frontiers in Artificial Intelligence and Applications, page 21-39. IOS Press, (2007)Aggregating Similar Witnesses for Flexible Query Answering., and . FQAS, volume 7 of Advances in Soft Computing, page 220-229. Physica-Verlag Heidelberg New York, A Springer-Verlag Company, (2000)Evaluation of Models for Semantic Information Filtering., and . IHCI, volume 179 of Advances in Intelligent Systems and Computing, page 221-229. Springer, (2011)Interpreting Web Shop User's Behavioral Patterns as Fictitious Explicit Rating for Preference Learning., and . RuleML, volume 8620 of Lecture Notes in Computer Science, page 251-265. Springer, (2014)A Data Model for Flexible Querying., and . ADBIS, volume 2151 of Lecture Notes in Computer Science, page 280-293. Springer, (2001)Soundness and Completeness of Non-classical SLD-Resolution., and . ELP, volume 1050 of Lecture Notes in Computer Science, page 289-301. Springer, (1996)Off-line vs. On-line Evaluation of Recommender Systems in Small E-commerce., and . HT, page 291-300. ACM, (2020)Using Implicit Preference Relations to Improve Recommender Systems., and . J. Data Semant., 6 (1): 15-30 (2017)Translation of Ontology Retrieval Problem into Relational Queries., , and . DATESO, volume 471 of CEUR Workshop Proceedings, page 44-55. CEUR-WS.org, (2009)