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Unbiased-Weighted-Crawl Algorithm Based Aggregate Estimation in Hidden Databases With Checkbox Interfaces

P Mallika, M Ashwin, A.M. Ravishankkar

Abstract


A large number of web data receptacles are hidden behind restrictive web interfaces, making it an important challenge to enable data analytics over these hidden web databases. This module is used to enabling the aggregate queries over a hidden database with checkbox interface by issuing a small number of queries (sampling) through its web interface. That this approach will be handled in both synthetic and real datasets demonstrate the accuracy and efficiency of the algorithms. To enable the approximation processing of aggregate queries and develops algorithm UNBIASED-WEBIGHTED-CRAWL which performs random drill-downs on a novel structure of queries which referred as a left-deep tree and also propose weight adjustment and low probability crawl to improve estimation accuracy.

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References


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