Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Folksonomy-based fuzzy user profiling for improved recommendations Subject The topic of the resource Content based recommender systems; Folksonomy; Fuzzy sets; Reclusive methods; Recommender system; Tags Description An account of the resource Genre is a major factor influencing user decisions to peruse an item in domains such as movies, books etc. Recommender systems, generally have, at their disposal, information regarding genres/categories that a movie/book belongs to. However, the degree of membership of the objects in these categories is typically unavailable. Such information, if available, would provide a better description of items and consequently lead to quality recommendations. In this paper, we propose an approach to infer the degree of genre presence in a movie by examining the various tags conferred on them by various users. Tags are user-defined metadata for items and embed abundant information about various facets of user likes, their opinion on the quality and the type of object tagged. Leveraging on tags to guide the genre degree determination exploits crowd sourcing to enrich item content description. Fuzzy logic naturally models human logic allowing for the nuanced representation of features of objects and thus is utilized to derive such gradual representation as well as for modeling user profiles. To the best of our knowledge ours is one of the first approaches to utilize such folksonomy information to infer genre degrees subsequently used for recommendations. The proposed method has the twin advantages of utilizing enriched content information for recommendation as well as squeezing the information from the user-item-tag and user-item ratings spaces and condensing them into fuzzy user profiles. The fuzzy user and object representations are leveraged both for the design of content-based as well as collaborative recommender systems. Experimental evaluations establish the effectiveness of the proposed approaches as compared to other baselines. 2013 Elsevier Ltd. All rights reserved. Creator An entity primarily responsible for making the resource Anand D.; Mampilli B.S. Source A related resource from which the described resource is derived Expert Systems with Applications, Vol-41, No. 5, pp. 2424-2436. Date A point or period of time associated with an event in the lifecycle of the resource 2014-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/j.eswa.2013.09.041" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.eswa.2013.09.041</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-84890118396&amp;doi=10.1016%2Fj.eswa.2013.09.041&amp;partnerID=40&amp;md5=0a3d06820760c8b15ff57b1db9df9444" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-84890118396&amp;doi=10.1016%2fj.eswa.2013.09.041&amp;partnerID=40&amp;md5=0a3d06820760c8b15ff57b1db9df9444</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 9574174; CODEN: ESAPE Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Anand D., CMR Institute of Technology, AECS Layout, Bangalore, Karnataka 560037, India; Mampilli B.S., Christ University, Bangalore, Karnataka 560029, Hosur Road, India