Publication
Title
Collaborative filtering for binary, positiveonly data
Author
Abstract
Traditional collaborative ltering assumes the availability of explicit ratings of users for items. However, in many cases these ratings are not available and only binary, positive-only data is available. Binary, positive-only data is typically associated with implicit feedback such as items bought, videos watched, ads clicked on, etc. However, it can also be the results of explicit feedback such as likes on social networking sites. Because binary, positive-only data contains no negative information, it needs to be treated differently than rating data. As a result of the growing relevance of this problem setting, the number of publications in this field increases rapidly. In this survey, we provide an overview of the existing work from an innovative perspective that allows us to emphasize surprising commonalities and key differences.
Language
English
Source (journal)
SIGKDD explorations
Publication
2017
ISSN
1931-0145
1931-0153
Volume/pages
19 :1 (2017) , p. 1-21
Full text (Publisher's DOI)
Full text (publisher's version - intranet only)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Record
Identification
Creation 12.12.2018
Last edited 15.07.2021
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