Paper Info
Title
A Linguistic Multi-Level Weighted Query Language To Represent User Information Needs
Abstract
An ordinal fuzzy linguistic Information Retrieval System (IRS) based on a multi-level weighting scheme to represent the user queries, in a more flexible way, is proposed. The IRS accepts Boolean queries that can be weighted simultaneously by means of ordinal linguistic values in two weighting levels: level of terms and level of connectives. In level of terms, the weights are associated to a threshold semantics, and in the level of connectives they are associated to a control semantics acting as modifiers of the action of the Boolean classical connectives AND and OR in the retrieval process. A new family of parameterized soft computing operators, called S-LOWA operators, is introduced for modelling that control semantics in the action of the connectives AND and OR.
Year
DOI
Venue
2007
10.1109/FUZZY.2007.4295558
2007 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-4
Keywords
Field
DocType
information retrieval, weighted queries, linguistic modelling
Rule-based machine translation,Query language,Weighting,Computer science,User information,Theoretical computer science,Natural language processing,Artificial intelligence,Ordinal number,Fuzzy logic,Boolean algebra,Linguistics,Semantics
Conference
ISSN
Citations 
PageRank 
1098-7584
0
0.34
References 
Authors
15
5
Name
Order
Citations
PageRank
Enrique Herrera-Viedma113105642.24
Antonio Gabriel López-herrera242318.65
Sergio Alonso3166953.28
Carlos Porcel445024.12
Francisco Javier Cabrerizo5165559.39