Exploiting Cross-Document Relations for Multi-document Evolving Summarization

TL;DR

This paper introduces a method for multi-document summarization that leverages cross-document relations among textual elements to generate focused summaries about a specific topic.

Contribution

It proposes a novel approach that specifies and identifies cross-document relations and messages to improve query-based multi-document summarization.

Findings

Effective identification of topic-specific entities and messages

Improved summarization quality through relation-based message linking

Framework adaptable to various topics and queries

Abstract

This paper presents a methodology for summarization from multiple documents which are about a specific topic. It is based on the specification and identification of the cross-document relations that occur among textual elements within those documents. Our methodology involves the specification of the topic-specific entities, the messages conveyed for the specific entities by certain textual elements and the specification of the relations that can hold among these messages. The above resources are necessary for setting up a specific topic for our query-based summarization approach which uses these resources to identify the query-specific messages within the documents and the query-specific relations that connect these messages across documents.