Cooperative strategy for web data mining and cleaning
While the Internet and World Wide Web have put a huge volume of low-quality information at the easy access of an information gathering system, filtering out irrelevant information has become a big challenge. In this paper, a Web data mining and cleaning strategy for information gathering is proposed. A data-mining model is presented for the data that come from multiple agents. Using the model, a data-cleaning algorithm is then presented to eliminate irrelevant data. To evaluate the data-cleaning strategy, an interpretation is given for the mining model according to evidence theory. An experiment is also conducted to evaluate the strategy using Web data. The experimental results have shown that the proposed strategy is efficient and promising.
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|Item Type:||Journal Article|
|Keywords:||Web mining, information fusion, information agents|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > LIBRARY AND INFORMATION STUDIES (080700) > Information Retrieval and Web Search (080704)|
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
|Copyright Owner:||Copyright 2003 Taylor & Francis|
|Copyright Statement:||First published in Applied Artificial Intelligence 17(5-6):pp. 443-460.|
|Deposited On:||19 Apr 2007|
|Last Modified:||22 Apr 2013 13:54|
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