Review: Evaluating and Analyzer to Developing Optimized Text Summary Algorithm
Madhuri Gawali1, Mrunal Bewoor2, Suhas Patil3
1Ms. Madhuri K. Gawali, Pursuing Master M.Tech, Department of Computer Engineering and Technology, Bharati Vidyapeeth Deemed University College of Engineering, Pune (Maharashtra), India.
2Mr. Mrunal Bewoor, Assistant Professor, Department of Computer Engineering and Technology, Bharati Vidyapeeth Deemed University College of Engineering, Pune (Maharashtra), India.
2Dr. Suhas Patil, Professor, Department of Computer Engineering and Technology, Bharati Vidyapeeth Deemed University College of Engineering, Pune (Maharashtra), India.
Manuscript received on 12 March 2013 | Revised Manuscript received on 21 March 2013 | Manuscript Published on 30 March 2013 | PP: 174-175 | Volume-2 Issue-4, March 2013 | Retrieval Number: D0586032413/13©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Information available on internet is in unstructured manner, retrieving relevant documents containing the required information is difficult. Due to huge amount of data, query specific document summarization has become an important problem. It is difficult task for the user to go through all these documents, as the number of documents available on particular topic will be more. It will be helpful for the user if query specific document summery is generated. Comparing different clustering algorithms those provide better result for summarization. Based on this we provide input as one query and get all the documents related to that and on these document different clustering algorithm are used to get results of each Algorithm. Then these algorithms comparing results with each other in terms of speed, memory, and quality of summary. After comparison we can decide which algorithm is better for summarization. So it will help to find the better query dependent clustering algorithm for text document summarization.
Keywords: Clustering, Summarization.
Scope of the Article: VLSI Algorithms