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
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