Citation Analysis

Abstract

Researchers have largely focused on analyzing citation links from one scholarly work to another. Such citing sentences are an important part of the narrative in a research article. If we can automatically identify such sentences, we can devise an editor that helps suggest when a particular piece of text needs to be backed up with a citation or not. In terms of this point, we propose a method for identifying citing sentences by constructing a classifier using supervised learning.

Publication

2017

Prasad, Animesh

WING-NUS at CL-SciSumm 2017: Learning from Syntactic and Semantic Similarity for Citation Contextualization Conference

Proceeding of the 2nd Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL@SIGIR), CEUR, Tokyo, Japan, 2017.

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An, Juyong ; Kim, Namhee ; Kan, Min-Yen ; Chandrasekaran, Muthu Kumar ; Song, Min

Exploring Characteristics of Highly Cited Authors according to Citation Location and Content Journal Article

Journal of the Association for Information Science and Technology, 2017.

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2010

Sugiyama, Kazunari; Kumar, Tarun; Kan, Min-Yen; Tripathi, Ramesh C

Identifying Citing Sentences in Research Papers Using Supervised Learning Conference

Proceedings of the 2010 International Conference on Information Retrieval and Knowledge Management (CAMP '10), 2010.

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