Work place: Department of Computer Science and Computer Application, Vivekanandha College of Arts and Sciences for Women (Autonomous), India
E-mail: suryaamca88@gmail.com
Website:
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Biography
Surya S. is an accomplished scholar and researcher, holds a Master's degree in Computer Applications (MCA) and an M. Phil. Currently pursuing a Ph.D. at the PG and Research Department of Computer Science and Computer Applications in Vivekanandha College of Arts and Sciences for Women (Autonomous), situated in Elayampalayam, Tiruchengode, Namakkal District, Tamil Nadu.
DOI: https://doi.org/10.5815/ijmecs.2024.04.05, Pub. Date: 8 Aug. 2024
This work proposes a Query Searching Based Ranking Summarization Data Retrieval (QS-RSDR) method for document summarization based on information retrieval. QS-RSDR ranks query-based retrieval of important information, enabling the creation of a detailed report of information requirements using generated sections of sample documents. Relating Keyword Query Search Summarization (RKQSS) generates the main summary from the most relevant document in the query and then the summary from the other documents. The method resolves similarity terms related to the query using the Word Frequency (WF) method. Sentence ranking weights and sentence frequency improve the accuracy of the retrieved documents. Simulation results show improved accuracy in information retrieval. The proposed method can help address unclear and short queries and understand the nature of the required information behind the query. The paper concludes that QS-RSDR is an effective solution for document summarization based on information retrieval using the query search ranking method.
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