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Semantic Features from Web-Traffic Streams

  • Steve Hutchinson
Chapter
Part of the Advances in Information Security book series (ADIS, volume 55)

Abstract

We describe a method to convert web-traffic textual streams into a set of documents in a corpus to allow use of established linguistic tools for the study of semantics, topic evolution, and token-combination signatures. A novel web-document corpus is also described which represents semantic features from each batch for subsequent analysis. A (American-English) lexicon is used to create a canonical representation of each corpus whereby there is a consistent mapping of each TermID to the corresponding lexicon-word or token. Finally, representation of a corpus member as a ‘document’ is accomplished by combining the (http) request string with the concatenation of all responses to it. This representation thus allows association of the request string tokens with the resulting content, for consumption by document classification and comparison algorithms.

Keywords

Semantic Analysis Latent Dirichlet Allocation Document Classification Corpus Member Stopword List 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.ICF International Fairfax USA

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