AAAI Publications, Workshops at the Twenty-Sixth AAAI Conference on Artificial Intelligence

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What's in a URL? Genre Classification from URLs
Myriam Abramson, David W. Aha

Last modified: 2012-07-15


The importance of URLs in the representation of a document cannot be overstated. Shorthand mnemonics such as ``wiki'' or ``blog'' are often embedded in a URL to convey its functional purpose or genre. Other mnemonics have evolved from use (e.g., a Wordpress particle is strongly suggestive of blogs). Can we leverage from this predictive power to induce the genre of a document from the representation of a URL? This paper presents a methodology for webpage genre classification from URLs which, to our knowledge, has not been previously attempted. Experiments using machine learning techniques to evaluate this claim show promising results and a novel algorithm for character n-gram decomposition is provided. Such a capability could be useful to improve personalized search results, disambiguate content, efficiently crawl the Web in search of relevant documents, and construct behavioral profiles from clickstream data without parsing the entire document.


Genre Classification; n-grams; URL; Naive Bayes

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