Scientific Paper Summarization Using Citation Summary Networks

TL;DR

This paper introduces a model for summarizing scientific articles by analyzing citation networks and clustering citation summaries to capture different viewpoints, aiding researchers in quickly understanding new research areas.

Contribution

The paper presents a novel citation summary network-based model for summarizing individual scientific articles, which can be extended to summarize entire research topics.

Findings

Effective citation network clustering reveals diverse viewpoints.

Model improves understanding of article contributions.

Applicable to summarizing large bodies of scientific literature.

Abstract

Quickly moving to a new area of research is painful for researchers due to the vast amount of scientific literature in each field of study. One possible way to overcome this problem is to summarize a scientific topic. In this paper, we propose a model of summarizing a single article, which can be further used to summarize an entire topic. Our model is based on analyzing others' viewpoint of the target article's contributions and the study of its citation summary network using a clustering approach.