DocumentCode :
2637044
Title :
Evolutionary machine learning for Web mining
Author :
Joshi, Amruta ; Todwal, Sapna
Author_Institution :
Pune Inst. of Comput. Technol., India
Volume :
2
fYear :
2003
fDate :
15-17 Oct. 2003
Firstpage :
693
Abstract :
The Internet is an extensive source of information and searching it exhaustively is inefficient in terms of time complexity. Web search is one of the most universal and influential applications on the Internet. A new search mechanism called SmartSeek is introduced. Inspired by machine learning concepts, this new technique employs a genetic algorithm (GA) for adapting to the user´s interests. The system accepts user feedback for fitness evaluation. The mutation operation involved in the process ensures that the search is not confined to a limited domain.
Keywords :
Internet; data mining; feedback; genetic algorithms; information retrieval; learning (artificial intelligence); Internet; SmartSeek; Web mining; Web search; evolutionary machine learning; fitness evaluation; genetic algorithm; time complexity; Artificial intelligence; Data mining; Genetic programming; Humans; Internet; Learning systems; Machine learning; Uniform resource locators; Web mining; Web search;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
TENCON 2003. Conference on Convergent Technologies for the Asia-Pacific Region
Print_ISBN :
0-7803-8162-9
Type :
conf
DOI :
10.1109/TENCON.2003.1273268
Filename :
1273268
Link To Document :
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