Ranking user-created contents by search user's inclination in online communities

ABSTRACT

Searching posts effectively has become an important issue in large-scale online communities. Especially, if search users have different inclinations when they search posts, they have different kinds of posts in their minds. To address this problem, in this paper, we propose a scheme of ranking posts based on search users' inclination. User ranking score is employed to capture posts that are relevant to a specific user inclination. Specifically, we present a scheme to rank posts in terms of user expertise and popularity. Experimental results show that different user inclinations can produce quite different search results and the proposed scheme achieves about 70% accuracy.

REFERENCES

• 1: Hyoseop Shin , Zhiwei Xu , Eun-Yi Kim, Discovering and Browsing of Power Users by Social Relationship Analysis in Large-Scale Online Communities, Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, p.105-111, December 09-12, 2008 [doi>10.1109/WIIAT.2008.391]
• 2: Expertise/Popularity-based Community Search Demo, "http://webi.konkuk.ac.kr/ep_rank".
• 3: Julia Luxenburger , Shady Elbassuoni , Gerhard Weikum, Matching task profiles and user needs in personalized web search, Proceeding of the 17th ACM conference on Information and knowledge management, October 26-30, 2008, Napa Valley, California, USA [doi>10.1145/1458082.1458175]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Information filtering

General Terms:
Algorithms

Keywords:
expertise, online community, popularity, post ranking, search user inclination, user ranking