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Frequency : 12 issues per year
Subject : Computer Applications and Technology
ISSN : 2319–8656 (Online)
Home Archives Volume 9 Issue 8 ijcatr09081005

IJCATR Volume 9 Issue 8

Document Summarization using Graph Based Methodology

Aditya Jeswani, Shruti More, Kabir Kapoor, Sifat Sheikh, Ramchandra Mangrulkar
10.7753/IJCATR0908.1005
keywords : Extractive summarization, Multi-document summarization, Key phrase extraction, Shortest path algorithm, Textrank algorithm, GloVe embeddings, Cosine similarity.

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This paper works towards constructing a short summary of documents with the help of natural language processing techniques. The authors goal is to identify the important aspects of a large piece of textual information, extract it and present it in a concise manner such that it conveys the information in a more efficiently and precisely. The proposed approach will generate a simple summarization of one or more documents which will help the readers to understand what the documents offer to them and identify their context without reading through them entirely. The existing methods for this work focus on different aspects of the text involved but the efficiency of these methods largely varies. The proposed methodology makes use of a combination of multiple aspects of text instead of a single aspect in order to improve the efficiency of summarization systems. The authors present a qualitative and quantitative analysis of their system as compared to the existing base-lines and demonstrate our system for a relevant application like news snippet generation.
@artical{a982020ijcatr09081005,
Title = "Document Summarization using Graph Based Methodology",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "9",
Issue ="8",
Pages ="240 - 245",
Year = "2020",
Authors ="Aditya Jeswani, Shruti More, Kabir Kapoor, Sifat Sheikh, Ramchandra Mangrulkar"}
  • The paper proposes a graph-based approach to extract sentences for summaries
  • Pronouns in the sentences are resolved to remove ambiguity and get appropriate keywords
  • A modified Dijkstra’s Shortest Path algorithm is used to reduce the corpus to be processed
  • The summaries are tested using ROUGE measures to evaluate the performance of the model.
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