Considering the rapidly increasing mass of information on the Web, the quality of documents is a very critical issue in Web information retrieval. This paper presents the importance of surface linguistic features in predicting the quality of user generated documents. A machine learning approach to incorporating surface linguistic features in predicting of document quality is tested on a collection of answers gathered from a community-driven knowledge search service that allows users to ask and answer questions posed by other users. Experimental results show that the features are useful for predicting the quality of answers.
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