Clustering of Short Commercial Documents for the Web

Document clustering techniques have been applied in several areas, with the web as one of the most recent and influent. Both general-purpose and text-oriented techniques exist and can be used to cluster a collection of documents in many ways. In this work we propose a single-pass document clustering model that can be combined with a variety of text-oriented similarity measures. An experimental evaluation of the proposed model was conducted in the e-commerce domain. Performances were measured using a clustering-oriented metric based on F-Measure and compared with those obtained by other well-known approaches.