The evolution of the World Wide Web has brought us enormous amounts of information for business and research use. Design and implementation of an automated system for Web data mining has become important for companies wishing to utilize useful information from the Web. We attempt to describe confidence on approximate queries on large datasets, which is done in the context of an automated system for Web data mining. The system has been designed to identify, extract, filter, and analyze data from Web resources. An approach to evaluating the quality of extracted Web data is also discussed. This is an exploratory study of Web data retrieval and Web data analysis.
['Charles Wesley Ford', 'Chia-Chu Chiang', 'Hao Wu', 'Radhika R. Chilka', 'John Talburt']
Confidence on approximate query in large datasets