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International Journal on Digital Libraries

Erschienen in:

13.06.2017

Computational linguistics literature and citations oriented citation linkage, classification and summarization

verfasst von: Lei Li, Liyuan Mao, Yazhao Zhang, Junqi Chi, Taiwen Huang, Xiaoyue Cong, Heng Peng

Erschienen in: International Journal on Digital Libraries | Ausgabe 2-3/2018

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Abstract

Scientific literature is currently the most important resource for scholars, and their citations have provided researchers with a powerful latent way to analyze scientific trends, influences and relationships of works and authors. This paper is focused on automatic citation analysis and summarization for the scientific literature of computational linguistics, which are also the shared tasks in the 2016 workshop of the 2nd Computational Linguistics Scientific Document Summarization at BIRNDL 2016 (The Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries). Each citation linkage between a citation and the spans of text in the reference paper is recognized according to their content similarities via various computational methods. Then the cited text span is classified to five pre-defined facets, i.e., Hypothesis, Implication, Aim, Results and Method, based on various features of lexicons and rules via Support Vector Machine and Voting Method. Finally, a summary of the reference paper from the cited text spans is generated within 250 words. hLDA (hierarchical Latent Dirichlet Allocation) topic model is adopted for content modeling, which provides knowledge about sentence clustering (subtopic) and word distributions (abstractiveness) for summarization. We combine hLDA knowledge with several other classical features using different weights and proportions to evaluate the sentences in the reference paper. Our systems have been ranked top one and top two according to the evaluation results published by BIRNDL 2016, which has verified the effectiveness of our methods.

Vorheriger Artikel Insights from CL-SciSumm 2016: the faceted scientific document summarization Shared Task

Nächster Artikel Identifying reference spans: topic modeling and word embeddings help IR

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Titel: Computational linguistics literature and citations oriented citation linkage, classification and summarization
verfasst von: Lei Li
Liyuan Mao
Yazhao Zhang
Junqi Chi
Taiwen Huang
Xiaoyue Cong
Heng Peng
Publikationsdatum: 13.06.2017
Verlag: Springer Berlin Heidelberg
Erschienen in: International Journal on Digital Libraries / Ausgabe 2-3/2018
Print ISSN: 1432-5012
Elektronische ISSN: 1432-1300
DOI: https://doi.org/10.1007/s00799-017-0219-5

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