Single Document Extractive Summarization using Domination in Hypergraph
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Computer Science > Computation and Language
Title:Single Document Extractive Summarization using Domination in Hypergraph
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
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Submission history
From: Sheetal Sonawane Dr [view email][v1] Wed, 8 Jul 2026 09:46:49 UTC (478 KB)
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