NDLI: On Finding Fine-Granularity User Communities by Profile Decomposition

Content Provider	IEEE Xplore Digital Library
Author	Seulki Lee Minsam Ko Keejun Han Jae-Gil Lee
Copyright Year	2012
Description	Author affiliation: Dept. of Knowledge Service Eng., Korea Adv. Inst. of Sci. & Technol., Daejeon, South Korea (Seulki Lee; Minsam Ko; Keejun Han; Jae-Gil Lee)
Abstract	The social network represents various relationships between users, and community discovery is one of the most popular tasks analyzing these relationships. The relationships are either explicit (e.g., friends) or implicit, and we focus on community discovery with implicit relationships. Here, the key issue is how to extract the relationships between users. A user is typically represented by his/her profile, and the similarity between user profiles is measured. In most algorithms, a user has a single profile aggregating all the information about the user. For example, a profile for a researcher is a list of papers he/she wrote. This setting, however, oversimplifies the multiple characteristics of a man since individual characteristics are mixed up. In this paper, we propose the notion and method of profile decomposition, which divides a profile into a set of sub-profiles so that they represent individual characteristics precisely. Then, we develop a community discovery algorithm, which we call DecompClus, based on profile decomposition. Using a real data set of CiteULike, we show that our proposed algorithm can precisely distinguish multiple research interests of a user and discover communities corresponding to each interest, whereas previous algorithms cannot. Overall, profile decomposition enables us to find fine-granularity user communities, thus improving the accuracy of community discovery.
Sponsorship	IEEE Comput. Soc.
Starting Page	631
Ending Page	639
File Size	499742
Page Count	9
File Format	PDF
ISBN	9781467324977
DOI	10.1109/ASONAM.2012.106
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-26
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis social network user profile profile decomposition Social network services Communities Clustering algorithms community discovery Vectors Partitioning algorithms Data mining
Content Type	Text
Resource Type	Article

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