Extarctive Summarization Of Farsi Documents Based On PSO Clustering

Automatic text summarization systems aim to make their created summaries closer to human summaries. The summary creation under the conditionof the redundancy and the summary length limitation is a challengeproblem. Two important kind of textual dependencies are Cohesion and Coherence. Cohesion is the relation between two textual components which they tend to hang together, while coherence refers to the fact that there is sense (or intelligibility) in a text. Actually, coherence has higher level rather than cohesion because it is more complex to detect coherence rather than cohesion. In this paper,we present a Particle Swarm Optimization (PSO) Sentences clustering algorithm. Contrary to thelocalized searching of the K-means algorithm, the PSO clustering algorithm performs a globalized search inthe entire solution space. In the experiments we conducted, The implementation of the proposed method is shown good results on a large corpus of news from ISNA.