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Quest: An Adaptive Framework for User Profile Acquisition from Social Communities of Interest
KTH, School of Information and Communication Technology (ICT), Communication: Services and Infrastucture, Software and Computer Systems, SCS.
Norwegian University of Science and Technology.ORCID iD: 0000-0002-4722-0823
2010 (English)In: Proceedings - 2010 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2010, 2010, 360-364 p.Conference paper (Refereed)
Abstract [en]

Within this paper we introduce a framework for semi- to full-automatic discovery and acquisition of bag-of-words style interest profiles from openly accessible Social Web communities. To do such, we construct a semantic taxonomy search tree from target domain (domain towards which we're acquiring profiles for), starting with generic concepts at root down to specific-level instances at leaves, then we utilize one of proposed Quest methods, namely Depth-based, N-Split and Greedy to read the concept labels from the tree and crawl the source Social Network for profiles containing corresponding topics. Cached profiles are then mined in a two-step approach, using a clusterer and a classifier to generate predictive model presenting weighted profiles, which are used later on by a semantic recommender to suggest and recommend the community members with the items of their similar interest.

Place, publisher, year, edition, pages
2010. 360-364 p.
Keyword [en]
Adaptive crawling, Profile mining, Social network analysis, User profiles
National Category
Computer Science
URN: urn:nbn:se:kth:diva-74861DOI: 10.1109/ASONAM.2010.67ScopusID: 2-s2.0-77958190948ISBN: 978-0-7695-4138-9OAI: diva2:490127
2010 International Conference on Advances in Social Network Analysis and Mining, ASONAM 2010; Odense; 9 August 2010 through 11 August 2010
QC 20120306Available from: 2012-02-03 Created: 2012-02-03 Last updated: 2013-02-20Bibliographically approved

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Dokoohaki, NimaMatskin, Mihhail
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ReferencesLink to record
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