PIST: A P2P IR Model for Social-Tagging Network

Author

Zhenhua, Wang ; Derong, Shen ; Ge, Yu

Author_Institution

Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China

fYear

2009

fDate

18-20 Sept. 2009

Firstpage

143

Lastpage

146

Abstract

This paper proposes a P2P information retrieval model for social-tagging network (PIST), which is layered on top of a DHT-based overlay network. The tags of document, user´s friends, interests and feedback are exploited to improve the search performance. With the help of friends, the user can get his desired documents with one-hop access. A document is associated with a document profile consisting of tags which describes the document. A user is associated with user profiles which represent his interests. During query processing, the relevant results can be returned according to user´s interest, and user´s feedback is exploited to refine the profiles and friends list. Experiments show that PIST has good performance and it is suitable for social-tagging network.

Keywords

document handling; information retrieval; peer-to-peer computing; social networking (online); table lookup; DHT-based overlay network; P2P IR model; P2P information retrieval model; PIST; document profile; one-hop access; query processing; search performance; social-tagging network; user profiles; Educational institutions; Feedback; Indexing; Information retrieval; Information science; Information systems; Peer to peer computing; Query processing; Search engines; Tagging; P2P IR; PIST; social-tagging network;

fLanguage

English

Publisher

ieee

Conference_Titel

Web Information Systems and Applications Conference, 2009. WISA 2009. Sixth

Conference_Location

Xuzhou, Jiangsu

Print_ISBN

978-0-7695-3874-7

Type

conf

DOI

10.1109/WISA.2009.22

Filename

5368051