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arXiv · 2609.15993

Single Document Extractive Summarization using Domination in Hypergraph

Aamir Miyajiwala·Aabha Pingle·Sheetal Sonawane·Surajit Kr. Nath
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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.

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Aamir Miyajiwala, Aabha Pingle, Sheetal Sonawane, Surajit Kr. Nath. 2026-07-08. Single Document Extractive Summarization using Domination in Hypergraph. https://arxiv.org/abs/2609.15993

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