122 International Journal for Modern Trends in Science and Technology International Journal for Modern Trends in Science and Technology, 6(11): 122-125, 2020 Copyright © 2020 International Journal for Modern Trends in Science and Technology ISSN: 2455-3778 online DOI: https://doi.org/10.46501/IJMTST061122 Available online at: http://www.ijmtst.com/vol6issue11.html A Semantic Text Summarization Method using ontology based Knowledge Dr.A.Mekala Department of BCA, Sacred Heart College To Cite this Article Dr.A.Mekala, “A Semantic Text Summarization Method using ontology based Knowledge”, International Journal for Modern Trends in Science and Technology, 6(11): 122-125, 2020. Article Info Received on 18-October-2020, Revised on 10-November-2020, Accepted on 19-November-2020, Published on 22-November-2020. Data mining is a method which finds useful patterns from large amount of data. As vast amounts of information are created quickly, effective information access becomes an important matter. Particularly for important domains, such as health check and monetary areas, well-organized recovery of succinct and related information is highly desired. In this paper we propose a new user query based text summarization technique that makes use of WordNet, a common information source from Princeton University. Our summarization structure is expressly tuned to recapitulate health care documents. KEYWORDS: WordNet, Text Summarization, Information Retrieval I. INTRODUCTION Text summarization is the crisis of creating a short, precise, and flowing outline of a longer text file. Automatic text summarization methods are really essential to speak to the ever-growing quantity of text data accessible online to together enhanced help determine relevant in sequence and to consume relevant in sequence earlier. in sequence plays a key role in our humanity. As enormous amounts of knowledge are created and accessible through WWW, how to powerfully and effectively distribute and admittance these valuable data becomes critical. A common Web search engine tries to give out as an information access agent. It retrieves and position in order according to a user’s query, and it previously makes a giant impact on how we search and organize information. But present search engines only achieve petty string processing owing to the lack of deep understanding of usual languages and human intelligence, and users usually have to go through pages before they find something useful or provide up. It may not matter much if user wants in order about a couple of shoes, but it will be a serious difficulty for crucial tasks, such as in medical or else. II. METHODOLOGY Information recovery systems consist of many intricate workings. Investigate and progress of such systems is often hindered by the intricacy in evaluating how each particular section would behave across many systems. We present a work of fiction integrated information retrieval system—the Query, Cluster, Summarize (QCS) system which is portable, modular, and permits carrying out tests with dissimilar instantiations of each of the constituent text analysis components. Most prominently, the grouping of the three types of methods in the QCS design improves retrievals by given that users more focused information well thought-out by topic. HelpfulMed HelpfulMed provides admission to health check information on the Internet and in medical-related ABSTRACT