Generating Summaries Using Sentence Compression and Statistical Measures

In this paper, we propose a compression based multi-document summarization technique by incorporating word bigram probability and word co-occurrence measure. First we implemented a graph based technique to achieve sentence compression and information fusion. In the second step, we use hand-crafted rule based syntactic constraint to prune our compressed sentences. Finally we use probabilistic measure while exploiting word co-occurrence within a sentence to obtain our summaries. The system can generate summaries for any user-defined compression rate.