Summarize-AI

Author(s)	Khaizar Kanchwala, Pallavi Maddula, Khaja Boqthiyar, P. Nageswara Rao
Country	India
Abstract	Text summarization is a system which generates a shorter and a precise form of one or further textbook documents. Automatic textbook summarization plays an essential part in chancing information from large textbook corpus or an internet. What had actually started as a single document Text Summarization has now evolved and developed into generating multi-document summarization. There are a number of approaches to multi document summarization similar as Graph, Cluster, Term-frequency, idle Semantic Analysis (LSA) grounded etc. In this paper we've started with preface of multi-document summarization and also have further bandied comparison and analysis of colorful approaches which comes under the multi-document summarization. The paper also contains details about the benefits and problems in the being styles. This would especially be helpful for experimenters working in this field of textbook data mining. By using this data, experimenters can make new or mixed grounded approaches for multi document summarization.
Keywords	Text summarization, cluster, multidocument summarization, graph, LSA, TermFrequency Based.
Field	Engineering
Published In	Volume 7, Issue 3, May-June 2025
Published On	2025-06-19
DOI	https://doi.org/10.36948/ijfmr.2025.v07i03.48528
Short DOI	https://doi.org/g9qxbd

About IJFMR Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+91-9687-828-838	editor@ijfmr.com

International Journal For Multidisciplinary Research