A General Bio-inspired Method to Improve the Short-Text Clustering Task

"Short-text clustering" is a very important research field due to the current tendency for people to use very short documents, e.g. blogs, text-messaging and others. In some recent works, new clustering algorithms have been proposed to deal with this difficult problem and novel bio-inspired methods have reported the best results in this area. In this work, a general bio-inspired method based on the AntTree approach is proposed for this task. It takes as input the results obtained by arbitrary clustering algorithms and refines them in different stages. The proposal shows an interesting improvement in the results obtained with different algorithms on several short-text collections.

• Type: Conference
• Year: 2010
• Where: CICLING
• Authors: Diego Ingaramo, Marcelo Errecalde, Paolo Rosso
• Keywords: Arbitrary Clustering Algorithms, Bio-inspired Method, CICLING 2010, Clustering Algorithms, Natural Language Processing