DocumentCode
162497
Title
IPM-G: Enabling Collaborative Filtering Using Multi-Application Interest Models
Author
Zhurong Zhou ; Jayarathna, Sampath ; Patra, Abani ; Shipman, Frank
Author_Institution
Comput. & Inf. Sci., Southwest Univ. Beibei, Chongqing, China
fYear
2014
fDate
27-29 Aug. 2014
Firstpage
141
Lastpage
144
Abstract
He Interest Profile Manager (IPM) plays the central role in inferring user interest during document triage. The IPM collects information about interest-related activity from the potentially many triage applications. In this paper, we extend the IPM framework to enable community-based navigation using inferred user interests from information gathering tasks involving the use of multiple applications. We call IPM running on server, Global IPM (IPM-G), and IPM-G can generate similarity assessments, and thus recommendations, based on three different levels: tasks, documents, and annotations. As a result, CF methods can be applied to each level to get results at these three levels of granularity. By representing inferred interests based on the features of their tasks, documents, and annotations, we make possible six potential collaborative filtering (CF) modes in the IPM-G. This paper describes why collaborative filtering based on multi-application interest models is important, abstractly describes the representation of the interest models, and presents details of one of these filtering modes.
Keywords
collaborative filtering; relevance feedback; CF methods; IPM-G; collaborative filtering; community-based navigation; document triage; global IPM framework; interest profile manager; interest-related activity; multiapplication interest models; similarity assessments; Collaboration; Computer architecture; Data models; Organizing; Recommender systems; Visualization; Collaborative filtering; relevance feedback; user interest modeling;
fLanguage
English
Publisher
ieee
Conference_Titel
Semantics, Knowledge and Grids (SKG), 2014 10th International Conference on
Conference_Location
Beijing
Type
conf
DOI
10.1109/SKG.2014.17
Filename
6964680
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