Open AccessDocument Summarization Using Clustering and Text Analysis
Author(s) -
Shahina Bano,
B Divyanjali,
A K M L R V Virajitha,
Mali Tejaswi
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.32.15740
Subject(s) - automatic summarization , computer science , cluster analysis , document clustering , information retrieval , redundancy (engineering) , multi document summarization , similarity (geometry) , text graph , reading (process) , term (time) , natural language processing , data mining , artificial intelligence , physics , quantum mechanics , political science , law , image (mathematics) , operating system
Document summarization is a procedure of shortening the content report with a product, so as to make the outline with the significant parts of unique record.Now a days ,users are very much tired about their works and they don’t have much time to spend reading a lot of information .they just want the maximum and accurate information which describes everything and occupies minimum space.This paper discusses an important approach for document summarization by using clustering and text analysis. In this paper, we are performing the clustering and text analytic techniques for reducing the data redundancy and for identifying similarity sentences in text of documents and grouping them in cluster based on their term frequency value of the words. Mainly these techniques help to reduce the data and documents are generated with high efficiency.