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Conference Paper Building a Topic Hierarchy from a Data Stream for Conceptualizing User Interest Profiles
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Authors
Hyun Namgoong, Kang Yong Lee, Kee Seong Cho, Jinuk Jung, Hong-Gee Kim
Issue Date
2012-10
Citation
International Conference on Information and Communication Technology Convergence (ICTC) 2012, pp.253-254
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICTC.2012.6386832
Abstract
Recent information technologies have produced a lot of user- participating community services, or Social Network Services (SNSs), and have received much attention as a pipeline of user behavioral information. This paper explains the conceptualization of a user interest profile (UIP) through a topic hierarchy, which learns topics and keywords from a domain data stream. The conceptualization enriches a UIP, consisting of user interests modeled as terms and term-weight, by providing contextual information of the UIP. For this, the topic hierarchy extracts topic-deterministic keywords and their semantic associations with domain topics, and thus the user keywords are converted into domain topics representing the context of user behaviors. This paper describes an empirical method to build a news topic hierarchy and its use for conceptualizing a series of keywords appearing in user SNS messages. © 2012 IEEE.
KSP Keywords
Community Service, Contextual information, Data stream, Empirical Methods, Interest profile, Social Network Service, Topic hierarchy, User Behavior, information technology, social network(SN), user interest