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Cluster Computing

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02-06-2017

Extracting reference text from citation contexts

Authors: Afsheen Khalid, Fakhri Alam, Imran Ahmed

Published in: Cluster Computing | Issue 1/2018

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Abstract

Information from the textual context of citations in scientific articles has been studied and used in many applications by the research community. For example, it has been used in topic modeling, sentiment analysis, scientific paper summarization and information retrieval. However, these applications suffer the problem of right identification of citation context window and alternately use the text in a fixed size window around the citation mention. In this way, citation contexts may contain terms or other text that is not used for describing the citation and should not be included in the citation context. Identifying such non-reference text in the citation context is a non-trivial task, yet significant. In this paper, it is attempted to identify and remove the non-reference text from the citation contexts by developing a heuristic algorithm based on pruning the transition-based dependency parse tree. Evaluating the accuracy of our algorithm, results showed 77% macro-precision, 83% macro-recall and 80% F-macro for 88 research articles of testing dataset having varying number of citations. Additionally, we find that for many of the cited articles in our testing dataset, the number of objective citation contexts is more than subjective ones.

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Title: Extracting reference text from citation contexts
Authors: Afsheen Khalid
Fakhri Alam
Imran Ahmed
Publication date: 02-06-2017
Publisher: Springer US
Published in: Cluster Computing / Issue 1/2018
Print ISSN: 1386-7857
Electronic ISSN: 1573-7543
DOI: https://doi.org/10.1007/s10586-017-0954-9

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