DocumentCode :
2457288
Title :
Macro-clustering: improved information retrieval using fuzzy logic
Author :
Liyanage, Harshana ; Bandara, G.E.M.D.C.
Author_Institution :
Dept. of Comput. Sci. & Stat., Peradeniya Univ., Sri Lanka
fYear :
2004
fDate :
2-4 Sept. 2004
Firstpage :
413
Lastpage :
418
Abstract :
The World Wide Web contains a huge amount of unclassified data and its continuous growth has made it a complex domain for information retrieval. Current Web information retrieval (IR) systems (i.e., search engines) very often overload the user with irrelevant search results. This has forced the user to perform a certain level of analysis on the results returned. Web IR systems are currently one of the most researched areas in the computer industry. So far there have been many attempts to incorporate soft computing techniques such as fuzzy logic, neural networks, genetic algorithms, etc. This work focuses on how fuzzy logic can be introduced to IR systems. The current applications of fuzzy techniques are analyzed and a concept called "macro-clustering" is introduced as a solution for optimizing results of generalized search queries.
Keywords :
Internet; data mining; fuzzy logic; information retrieval; World Wide Web; data mining; fuzzy logic; fuzzy macroclustering; information retrieval; soft computing techniques; Application software; Computer industry; Computer networks; Fuzzy logic; Genetic algorithms; Information retrieval; Neural networks; Performance analysis; Search engines; Web sites;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control, 2004. Proceedings of the 2004 IEEE International Symposium on
ISSN :
2158-9860
Print_ISBN :
0-7803-8635-3
Type :
conf
DOI :
10.1109/ISIC.2004.1387719
Filename :
1387719
Link To Document :
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