An online document clustering technique for short web contents

✍ Scribed by Moreno Carullo; Elisabetta Binaghi; Ignazio Gallo

• Book ID: 103879713
• Publisher: Elsevier Science
• Year: 2009
• Tongue: English
• Weight: 431 KB
• Volume: 30
• Category: Article
• ISSN: 0167-8655
• DOI: 10.1016/j.patrec.2009.04.001

✦ Synopsis

Document clustering techniques have been applied in several areas, with the web as one of the most recent and influential. Both general-purpose and text-oriented techniques exist and can be used to cluster a collection of documents in many ways. This work proposes a novel heuristic online document clustering model that can be specialized 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. The obtained results confirm the validity of the proposed method both for batch scenarios and online scenarios where document collections can grow over time.