In chapter 1, the main concept of text summarization and word sense disambiguation is introduced. Before starting Text summarization, first we, need to know that what a summary is. A summary can be defined as a non redundant text which gives important information of the original text, and is extracted from one or more sentences. We can say text summarization is the unique way, where a computer summarizes a text. A text is entered into the computer and a summarized text is returned as an output, which is a non redundant form of the original text. As the limit of Web pages on the Internet doubles everyday. It takes lots of time to get the relevant information. Automatic Text Summarization will find a way for users to find the relevant, redundant-less …show more content…
Similarly word summarization is also just like a text summarization in which we will give the text as a paragraph and from that text we can find the word summary using Word Sense Disambiguation technique.
1.3 Word sense disambiguation
Word Sense Disambiguation is a challenging technique in Natural Language Processing. There are some words in the natural languages which can cause ambiguity about the sense of the word. Those words are called polysemous words. Word sense disambiguation (WSD) is the solution to the problem. Word Sense Disambiguation is a task of automatically assigning a correct sense to the words which are polysemous in a particular context. WSD is mainly used in Information Retrieval (IR), Information Extraction (IE), Machine Translation (MT), Content Analysis, Word Processing, Lexicography and Semantic Web.
Word sense disambiguation consists of 2 steps:-
• Identify all the different senses for each word congruent to the text.
• It involves assigning relevant sense for each word in