Synopsizing “literature review” for scientific publications

Zhang, Lin; Liu, Xiaozhong

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https://hdl.handle.net/2142/89325 Copy

Description

Title

Synopsizing “literature review” for scientific publications

Author(s)

Zhang, Lin; Liu, Xiaozhong

Issue Date

2016-03-15

Keyword(s)

• citation clustering
• query-centric similarity
• citation summarization
• citation context
• publication representation

Abstract

Because the number of scientific publications in most disciplines is expanding rapidly, traditional academic search engines can hardly satisfy scholars’ need to retrieve and assimilate the information they are looking for. In this study we investigate a new summarization problem: creating a synopsis “Literature Review” of a collection of candidate cited papers in response to a query, via different methods and indicators. In more detail, we compare the use of different methods and indicators for generating citation clusters and summarized reviews by analyzing publication abstracts, citation contexts, and co-cite relationships. We also validate the usefulness of a user’s query during this process by comparing query-dependent and query-independent clustering and summarization. One interesting outcome of this study is that citation contexts are more suitable for clustering related papers, whereas abstracts are more accurate for generating longer review-like summaries. The initial user query is also helpful for enhancing clustering and summarization performance.

Publisher

iSchools

Series/Report Name or Number

IConference 2016 Proceedings

Type of Resource

text

Language

eng

Permalink

http://hdl.handle.net/2142/89325

DOI

https://doi.org/10.9776/16147

Copyright and License Information

Copyright 2016 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.

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