An efficient mobile social search method
Pages 82 - 85
Abstract
With the rapid development of internet technology, social networks and social searches are becoming popularly. Unlike traditional web searches, the social search provides optimal search results according to user preferences. In this paper, we propose a mobile social search method based on popularities and user preferences. The popularity is calculated by collecting the visiting records of users. The user preferences are generated by the actual visiting information among the search results. We process a skyline query to extract the meaningful information from the candidate objects with multiple features. The proposed method ranks social search results by combining user preferences and popularity with the skyline query processing mechanism. To show the superiority of the proposed method, we compare it with the existing method through performance evaluation.
References
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Index Terms
- An efficient mobile social search method
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Published In
October 2014
386 pages
ISBN:9781450330602
DOI:10.1145/2663761
- Conference Chairs:
- Chao Lu,
- Esmaeil Nadimi,
- Program Chairs:
- Sung-Ryul Kim,
- Wei Wang
Copyright © 2014 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
Sponsors
- Winway Systems: Winway Systems, Inc.
- SIGAPP: ACM Special Interest Group on Applied Computing
- ACCT: Association of Convergent Computing Technology
- TU: Towson University
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 05 October 2014
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RACS '14
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- Winway Systems
- SIGAPP
- ACCT
- TU
RACS '14: International Conference on Research in Adaptive and Convergent Systems
October 5 - 8, 2014
Maryland, Towson
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RACS '14 Paper Acceptance Rate 59 of 251 submissions, 24%;
Overall Acceptance Rate 393 of 1,581 submissions, 25%
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