Design and implementation for literature search and impact-based summaries

2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering Pub Date : 2010-11-01 DOI:10.1109/ISKE.2010.5680861

Chong Chen, Feng Li, Xianling Mao, Jing He, Hongfei Yan

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引用次数: 1

Abstract

Based on the PARADISE 1 (Platform for Applying, Researching and Developing Intelligent Search Engine), we construct a literature search engine with a collection of papers in computer network area. Besides retrieval, the system also provides comments and impact-based summaries of a paper. The comments are extracted from the citing papers and the summary is obtained from the paper sentences impacting on the citing papers. The functions give users a comprehensive knowledge about the paper they want. We first illustrate how to get candidate comment sentences from the citing papers and generate the citation contexts. Then a KL-divergence-based model is introduced to score the similarity between the sentences in the original paper and the citation contexts. The higher the score is, the more likely academic impact the sentence has. The top rank sentences are combined together as the paper's summary. The comment sentences are also selected for users to compare the details of related paper work. The experiment exposes the effect of the proposed implementation.

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设计和实现文献检索和基于影响的摘要

基于PARADISE 1(智能搜索引擎应用、研究与开发平台)，构建了一个包含计算机网络领域论文的文献搜索引擎。除了检索，系统还提供评论和基于影响的论文摘要。评语摘自被引论文，摘要摘自对被引论文有影响的论文句子。这些功能让用户对他们想要的论文有一个全面的了解。我们首先说明如何从引用论文中获取候选评论句子并生成引文上下文。然后引入基于kl发散度的模型对原文句子与引文上下文之间的相似度进行评分。分数越高，句子的学术影响就越大。将排名靠前的句子组合在一起作为论文的总结。还选择了评论句子，供用户比较相关论文工作的细节。实验表明了所提出的实现方法的效果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering

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