Description

Text summarization is the process of automatically creating a compressed version of a given document preserving its information content. Automatic document summarization is an important research area in natural language processing (NLP). The technology of automatic document summarization is developing and may provide a solution to the information overload problem. We focus on sentence based extractive document summarization. The extractive summarization systems are typically based on techniques for sentence extraction and aim to cover the set of sentences that are most important for the overall understanding of a given document. We will formalize the problem of text clustering with side information. The aim is to show that this approach is superior to natural clustering changes with the use of either pure text or with the use of both text and side data. The string Split method, which is an instance method on the string type, instead of regular expressions. That method is more appropriate for precise and predictable input.