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Probe, count, and classify: categorizing hidden web databases
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Source International Conference on Management of Data archive
Proceedings of the 2001 ACM SIGMOD international conference on Management of data table of contents
Santa Barbara, California, United States
Pages: 67 - 78  
Year of Publication: 2001
ISBN:1-58113-332-4
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Authors
Panagiotis G. Ipeirotis  Computer Science Dept., Columbia University
Luis Gravano  Computer Science Dept., Columbia University
Mehran Sahami  E.piphany, Inc.
Sponsor
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 7,   Downloads (12 Months): 88,   Citation Count: 37
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ABSTRACT

The contents of many valuable web-accessible databases are only accessible through search interfaces and are hence invisible to traditional web “crawlers.” Recent studies have estimated the size of this “hidden web” to be 500 billion pages, while the size of the “crawlable” web is only an estimated two billion pages. Recently, commercial web sites have started to manually organize web-accessible databases into Yahoo!-like hierarchical classification schemes. In this paper, we introduce a method for automating this classification process by using a small number of query probes. To classify a database, our algorithm 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 our technique over collections of real documents, including 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.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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CITED BY  37

Collaborative Colleagues:
Panagiotis G. Ipeirotis: colleagues
Luis Gravano: colleagues
Mehran Sahami: colleagues