Single Document Extractive Summarization using Domination in Hypergraph

基于超图支配集的单文档抽取式摘要

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.

摘要： 自然语言处理中的自动文本摘要（ATS）一直是信息检索领域的一项重要任务。它通过压缩文档来生成摘要，从而捕捉文档中传达的所有相关且重要的信息。本研究探讨了利用超图（Hypergraph）进行单文档的抽取式文本摘要。

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.

研究目标： 本研究探索了一种利用超图支配集（Domination）特性生成抽取式摘要的新方法，并将其性能与当前最先进的基于图的方法进行了比较。

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.

研究方法： 我们的工作旨在通过构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，而边则是包含该句子的关键词或命名实体。我们构建了一个超图，其中每条边代表一个关键词或重要主题，节点则是包含这些关键词的句子。随后，我们应用贪心算法来寻找超图的支配集，该集合中包含的句子将构成最终的抽取式摘要。