发表机构
SCTR’s Pune Institute of Computer Technology; Bodoland University（SCTR浦那计算机技术学院; 博多兰大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究提出利用超图支配集进行单文档抽取式摘要，通过构建句子-关键词超图并应用贪心算法寻找支配集，以生成覆盖重要信息的摘要，并与最先进的基于图的方法进行比较。
AI 中文摘要
自然语言处理中的自动文本摘要（ATS）一直是信息检索中的一项重要任务。它压缩文档以生成一个摘要，该摘要捕获文档中传达的所有相关且重要的信息。本研究探索将超图用于单文档的抽取式文本摘要。目标：本研究探索一种利用超图中支配性质生成抽取式摘要的新方法，并将其性能与最先进的基于图的方法进行比较。方法：我们的工作旨在通过创建句子超图来生成抽取式摘要，其中每个句子代表一个节点，边是一个关键词或命名实体，包含其出现的句子。我们生成一个超图，其中每条边是一个关键词或重要主题，节点是包含这些关键词的句子。然后，我们应用一种贪心算法来找到超图的支配集，该支配集将包含构成抽取式摘要的句子。
英文摘要
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.
Comments5 pages, 3 figures
