CAIS: Community based annotation insight search in a folksonomy network

Han Chang Huang, Hung-Yu Kao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Folksonomy systems provide a way for users to share and organize bookmarks. The social relationship among users has become stronger with the rapid development of new technologies. Finding the leading objects has become an important topic. These research topics are always centered around finding the most popular pages or experts. In this paper, we propose a new notion of expertise, which we call user insight. User insight denotes the user's expertise in finding Web pages that are useful or have the potential to be popular pages before other users find them. To address the issue, we refer to three major types of Web pages, namely, isolated, well-known, and burgeoning. Burgeoning pages are exceptionally useful and attractive for users in a folksonomy system. In our paper, we build a time-based algorithm to estimate user insight. In addition, we discuss the social relationship within fan networks, and we propose a link-based algorithm called CAIS (Community-based Annotation Insight Search) to realize the reinforcement between users, communities and pages. Finally, we design several experiments to evaluate the performance of CAIS and compare it to other approaches. We prove that CAIS has a better performance for the user ranking of simulated data and real data from Del.ici.ous.

Original languageEnglish
Title of host publicationProceedings - 2011 International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2011
Pages353-360
Number of pages8
DOIs
Publication statusPublished - 2011 Sep 19
Event2011 International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2011 - Kaohsiung, Taiwan
Duration: 2011 Jul 252011 Jul 27

Publication series

NameProceedings - 2011 International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2011

Other

Other2011 International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2011
CountryTaiwan
CityKaohsiung
Period11-07-2511-07-27

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'CAIS: Community based annotation insight search in a folksonomy network'. Together they form a unique fingerprint.

Cite this