Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

On text ranking for information retrieval based on degree of preference

Authors
Kang, B.Y.Kim, Dae-Won
Issue Date
Feb-2006
Publisher
SPRINGER-VERLAG BERLIN
Citation
COMPUTATIONAL LINGUISTICS AND INTELLIGENT TEXT PROCESSING, v.3878, pp 389 - 393
Pages
5
Journal Title
COMPUTATIONAL LINGUISTICS AND INTELLIGENT TEXT PROCESSING
Volume
3878
Start Page
389
End Page
393
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/40652
DOI
10.1007/11671299_40
ISSN
0302-9743
1611-3349
Abstract
A great deal of research has been made to model the vagueness and uncertainty in information retrieval. One such research is fuzzy ranking models, which have been showing their superior performance in handling the uncertainty involved in the retrieval process. However, these conventional fuzzy ranking models are limited to incorporate the user preference when calculating the rank of documents. To address this issue, we develop a new fuzzy ranking model based on the user preference.
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Software > School of Computer Science and Engineering > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Kim, Dae-Won photo

Kim, Dae-Won
소프트웨어대학 (소프트웨어학부)
Read more

Altmetrics

Total Views & Downloads

BROWSE