[Submitted on 8 Jul 2026]
Title:Single Document Extractive Summarization using Domination in Hypergraph
View a PDF of the paper titled Single Document Extractive Summarization using Domination in Hypergraph, by Aamir Miyajiwala and 2 other authors
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Abstract:Automatic Text Summarization (ATS) in Natural Language Processing has been an important task in Information Retrieval. It compresses a document to create a summary that captures all the relevant and important information conveyed in the document. This study explores Hypergraph for extractive text summarization of single documents. Objective: This study explores a novel method of leveraging the property of domination in hypergraphs to generate an extractive summary and compare its performance with state of the art graph based methods. Method: Our work aims to generate an extractive summary by creating a sentence hypergraph where each sentence represents a node and the edge is a keyword or a named entity that contains the sentences in which it occurs. We generate a hypergraph where each edge is a keyword or an important topic and the nodes are sentences containing those keywords. Then we apply a greedy algorithm to find the dominating set of the hypergraph which will contain sentences that will form the extractive summary.
Comments: 5 pages, 3 figures
Subjects:
Computation and Language (cs.CL); Machine Learning (cs.LG)
Cite as: arXiv:2609.15993 [cs.CL]
(or arXiv:2609.15993v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2609.15993
arXiv-issued DOI via DataCite
Submission history
From: Sheetal Sonawane Dr [view email] [v1] Wed, 8 Jul 2026 09:46:49 UTC (478 KB)
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View a PDF of the paper titled Single Document Extractive Summarization using Domination in Hypergraph, by Aamir Miyajiwala and 2 other authors
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