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Recommender Service for Social Network based Applications

Published: 12 August 2009 Publication History

Abstract

Social network based applications have grown dramatically in a tremendous amount such that requires a systematic approach to recommend suitable and attractive applications to the users in order to efficiently promote the visibility of application. In this paper, we propose a recommendation mechanism that 1) analyzes the social applications popularity and reputation by empirical study 2) calculates users preference based on data mining weighting methods 3) computes the applications social attraction power estimated from users social intimacy and interaction. Finally, a recommender system is implemented on one of the most famous social network websites- Facebook.

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cover image ACM Other conferences
ICEC '09: Proceedings of the 11th International Conference on Electronic Commerce
August 2009
407 pages
ISBN:9781605585864
DOI:10.1145/1593254
Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

  • School of Business, The University of Hong Kong, Hong Kong
  • Sayling Wen Cultural & Educational Foundation
  • Ministry of Education, Taiwan
  • College of Information Science and Technology, Drexel University, USA
  • Weatherhead School of Management, Case Western Reserve University, USA
  • College of Technology Management, National Tsing Hua University, Taiwan
  • National Science Council, Taiwan
  • Chinese Enterprise Resource Planning Society, Taiwan
  • International Center for Electronic Commerce, Korea Advanced Institute of Science & Technology, Korea

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 August 2009

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Author Tags

  1. AHP
  2. Application
  3. Recommendation
  4. Relation
  5. Social network

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  • Research-article

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ICEC '09
Sponsor:
ICEC '09: International Conference on E-Commerce
August 12 - 15, 2009
Taipei, Taiwan

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Overall Acceptance Rate 150 of 244 submissions, 61%

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