ITSA * : An Effective Iterative Method for Short-Text Clustering Tasks

The current tendency for people to use very short documents, e.g. blogs, text-messaging, news and others, has produced an increasing interest in automatic processing techniques which are able to deal with documents with these characteristics. In this context, “short-text clustering” is a very important research field where new clustering algorithms have been recently proposed to deal with this difficult problem. In this work, ITSA , an iterative method based on the bio-inspired method PAntSA is proposed for this task. ITSA takes as input the results obtained by arbitrary clustering algorithms and refines them by iteratively using the PAntSA algorithm. The proposal shows an interesting improvement in the results obtained with different algorithms on several short-text collections. However, ITSA can not only be used as an effective improvement method. Using random initial clusterings, ITSA outperforms well-known clustering algorithms in most of the experimental instances.