Extractive Summarization of a Document Using Lexical Chains

Nowadays, efficient access of information from the text documents with high-degree of semantic information has become more difficult due to diversity of vocabulary and rapid growth of the Internet. Traditional text clustering algorithms are widely used to organize a large text document into smaller manageable groups of sentences, but it does not consider the semantic relationship among the words present in the document. Lexical chains try to identify cohesion links between words by identifying their semantic relationship. They try to link words in a document that are thought to be describing the same concept to gather information. This method of text summarization helps to process the linguistic features of the document which is otherwise ignored in statistical summarization approaches. In this paper, we have proposed a text summarization technique by constructing lexical chains and defining a coherence metric to select the summary sentences.