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Tracking Web Spam with HTML Style Similarities
| Content Provider | CiteSeerX |
|---|---|
| Author | Lavergne, Thomas Chauveau, Emmanuel Urvoy, Tanguy Filoche, Pascal |
| Abstract | Automatically generated content is ubiquitous in the web: dynamic sites built using the threetier paradigm are good examples (e.g. commercial sites, blogs and other sites powered by a web authoring software), as well as less legitimate spamdexing attempts (e.g. link farms, faked directories...). Those pages built using the same generating method (template or script) share a common “look and feel ” that is not easily detected by common text classification methods, but is more related to stylometry. In this work we study and compare several html style similarity measures based on both textual and extra-textual features in html source code. We also propose a flexible algorithm to cluster a large collection of documents according to these measures. The algorithm we propose being based on locality sensitive hashing (lsh), we give some recalls about this technique. We describe how to use the html style similarity clusters to pinpoint dubious pages and enhance the quality of spam classifiers, and give an evaluation of our algorithm on the WEBSPAM-UK2006 dataset. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Good Example Threetier Paradigm Large Collection Dynamic Site Link Farm Commercial Site Flexible Algorithm Spam Classifier Legitimate Spamdexing Attempt Common Text Classification Method Html Source Code Webspam-uk2006 Dataset Common Look Web Spam Html Style Similarity Cluster Html Style Similarity Several Html Style Similarity Measure Locality Sensitive Hashing Dubious Page Extra-textual Feature |
| Content Type | Text |
