Enriching user search experience by mining social streams with heuristic stones and associative ripples

NCUIR > College of Electrical Engineering & Computer Science > Department of Computer Science and information Engineering > journal & Dissertation > Item 987654321/106731

Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/106731

Title:	Enriching user search experience by mining social streams with heuristic stones and associative ripples
Authors:	施國琛;Shih, Timothy K.;Jin, Qun;Yen, Neil Y.;Zhou, Xiaokang
Contributors:	資訊電機學院資訊工程學系
Date:	2013-03-01
Issue Date:	2026-04-23 13:38:54 (UTC+8)
Publisher:	Springer Netherlands;Springer Science and Business Media LLC
Abstract:	摘要： Recently, social networking sites such as Facebook and Twitter are becoming increasingly popular. The high accessibility of these sites has allowed the so-called social streams being spread across the Internet more quickly and widely, as more and more of the populations are being engaged into this vortex of the social networking revolution. Information seeking never means simply typing a few keywords into a search engine in this stream world. In this study, we try to find a way to utilize these diversified social streams to assist the search process without relying solely on the inputted keywords. We propose a method to analyze and extract meaningful information in accordance with users' current needs and interests from social streams using two developed algorithms, and go further to integrate these organized stream data which are described as associative ripples into the search system, in order to improve the relevance of the results obtained from the search engine and feedback users with a new perspective of the sought issues to guide the further information seeking process, which can benefit both search experience enrichment and search process facilitation. 出版者： Springer Science and Business Media LLC 出版日期： 2012-03-23 出處： Multimedia Tools and Applications, 2012-03, Vol.63, p.129-144 資源來源： ABI/INFORM Collection 識別號： ISSN: 1380-7501 識別號： EISSN: 1573-7721 識別號： DOI: 10.1007/s11042-012-1069-1
Appears in Collections:	[Department of Computer Science and information Engineering] journal & Dissertation

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