An angle-based interest model for text recommendation


Building an interest model is the key to realize personalized text recommendation. Previous interest models neglect the fact that a user may have multiple angles of interests. Different angles of interest provide different requests and criteria for text recommendation. This paper proposes an interest model that consists of two kinds of angles: persistence and pattern, which can be combined to form complex angles. The model uses a new method to represent the long-term interest and the short-term interest, and distinguishes the interest on object and the interest on the link structure of objects. Experiments with news-scale text data show that the interest on object and the interest on link structure have real requirements, and it is effective to recommend texts according to the angles.

Publication DOI:
Divisions: College of Engineering & Physical Sciences > School of Informatics and Digital Engineering > Computer Science
College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
Additional Information: © 2016, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Uncontrolled Keywords: text recommendation,interest model,multi-angle interest,Hardware and Architecture,Software,Computer Networks and Communications
Publication ISSN: 1872-7115
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2016-11
Published Online Date: 2016-05-09
Accepted Date: 2016-04-16
Submitted Date: 2016-03-18
Authors: Xu, Bei
Zhuge, Hai (ORCID Profile 0000-0001-8250-6408)

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