Classification-enhanced ranking

Many have speculated that classifying web pages can improve a search engine's ranking of results. Intuitively results should be more relevant when they match the class of a query. We present a simple framework for classificationenhanced ranking that uses clicks in combination with the classification of web pages to derive a class distribution for the query. We then go on to define a variety of features that capture the match between the class distributions of a web page and a query, the ambiguity of a query, and the coverage of a retrieved result relative to a query's set of classes. Experimental results demonstrate that a ranker learned with these features significantly improves ranking over a competitive baseline. Furthermore, our methodology is agnostic with respect to the classification space and can be used to derive query classes for a variety of different taxonomies. Categories and Subject Descriptors H.3.1 [Information Storage and Retrieval]: Content Analysis and Ind...

• Type: Conference
• Year: 2010
• Where: WWW
• Authors: Paul N. Bennett, Krysta Marie Svore, Susan T. Dumais
• Keywords: Class Distributions, Internet Technology, Ranking, Web Page, WWW 2010