Detecting Phrase-Level Duplication on the World Wide Web

Dennis Fetterly, Mark Manasse, and Marc Najork

Abstract

Two years ago, we conducted a study on the evolution of web pages over time. In the course of that study, we discovered a large number of machine-generated “spam” web pages emanating from a handful of web servers in Germany. These spam web pages were dynamically assembled by stitching together grammatically wellformed German sentences drawn from a large collection of sentences. This discovery motivated us to develop techniques for finding other instances of such “slice and dice” generation of web pages, where pages are automatically generated by stitching together phrases drawn from a limited corpus. We applied these techniques to two data sets, a set of 151 million web pages collected in December 2002 and a set of 96 million web pages collected in June 2004. We found a number of other instances of large-scale phrase-level replication within the two data sets. This paper describes the algorithms we used to discover this type of replication, and highlights the results of our data mining.

Details

Publication typeInproceedings
Published in28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
URLhttp://www.acm.org/
AddressSalvador, Brazil
PublisherAssociation for Computing Machinery, Inc.
> Publications > Detecting Phrase-Level Duplication on the World Wide Web