Academic Commons

Reports

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

Ipeirotis, Panagiotis G.; Gravano, Luis; Sahami, Mehran

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.

Subjects

Files

More About This Work

Academic Units
Computer Science
Publisher
Department of Computer Science, Columbia University
Series
Columbia University Computer Science Technical Reports, CUCS-010-01
Published Here
April 22, 2011