Show simple item record

dc.contributor.authorTkalčič M
dc.contributor.authorKošir A
dc.contributor.authorTasič JF
dc.contributor.other
dc.date.accessioned2018-08-01T09:07:58Z
dc.date.available2018-08-01T09:07:58Z
dc.date.issued2011
dc.identifier.isbn978-3-8443-3309-1
dc.identifier.urihttp://hdl.handle.net/10863/5367
dc.description.abstractThe growing amount of multimedia content is making it hard for end users to find the relevant content. The goal of recommender systems is to assist the users by finding a small subset of relevant multimedia items for each user. State-of-the-art techniques for recommending content are very data-centric. The progress beyond the state-of-the-art presented in this book consists in introducing new parameters based on emotions and personality that explain a substantial part of variance in the end users' preferences. The book covers the detection of emotions and personality factors of end users. The book then shows clearly how to use these user-centric data to model end users and thus improve the performance of a recommender system for images. The book will serve as a guideline and inspiration for practitioners and academics in content retrieval and affecting computing.en_US
dc.language.isoenen_US
dc.publisherLAP LAMBERT Academic Publishingen_US
dc.rights
dc.titleEmotive and personality parameters in recommender systems: Recognition and usage of user-centric data for user and item modeling in content retrieval systemsen_US
dc.typeBooken_US
dc.date.updated2018-05-16T07:37:06Z
dc.language.isiEN-GB
dc.description.fulltextreserveden_US


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record