QProber: A System for Automatic Classification of Hidden-Web Databases

Jan 2003

Authors: Luis Gravano, Panagiotis G. Ipeirotis, and Mehran Sahami

Venue: ACM Transactions on Information Systems (TOIS), Vol. 21, No. 1, January 2003

Abstract:

The contents of many valuable Web-accessible databases are only available through search interfaces and are hence invisible to traditional Web “crawlers.” Recently, commercial Web sites have started to manually organize Web-accessible databases into Yahoo!-like hierarchical classification schemes. Here we introduce QProber, a modular system that automates this classification process by using a small number of query probes, generated by document classifiers. QProber can use a variety of types of classifiers to generate the probes. To classify a database, QProber does not retrieve or inspect any documents or pages from the database, but rather just exploits the number of matches that each query probe generates at the database in question. We have conducted an extensive experimental evaluation of QProber over collections of real documents, experimenting with different types of document classifiers and retrieval models. We have also tested our system with over one hundred Web-accessible databases. Our experiments show that our system has low overhead and achieves high classification accuracy across a variety of databases.