DocumentCode
498211
Title
Abstract Recommendation with Assistance of Interactive User Profile Extraction
Author
Feng, Haodi ; Liu, Hong ; Lu, Shenpeng
Author_Institution
Sch. of Comput. Sci. & Technol., Shandong Univ., Jinan, China
Volume
1
fYear
2009
fDate
19-21 May 2009
Firstpage
239
Lastpage
243
Abstract
Abstraction and user-profile-based search are two important topics in information retrieval. In this paper, we combine these two problems together, and present a user-profile-based meta search system with which the user can read the abstracts of preferred documents. The user profile is represented as list of words, which are either given directly by the user or generated automatically by the system from the user´s reading history.
Keywords
information retrieval; meta data; abstract recommendation; information retrieval; interactive user profile extraction; meta search system; user reading history; Abstracts; Data mining; Feedback; History; Information retrieval; Internet; Metasearch; Search engines; Semantic Web; Web pages; abstraction; meta-search; user profile;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems, 2009. GCIS '09. WRI Global Congress on
Conference_Location
Xiamen
Print_ISBN
978-0-7695-3571-5
Type
conf
DOI
10.1109/GCIS.2009.100
Filename
5208983
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