文章基本信息

标题：A Comprehensive Evaluation of Cue-Words based Features and In-text Citations based Features for Citation Classification
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作者：Syed Jawad Hussain ; Sohail Maqsood ; NZ Jhanjhi 等
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2019
卷号：10
期号：7
页码：209-218
DOI：10.14569/IJACSA.2019.0100730
出版社：Science and Information Society (SAI)
摘要：Citation plays a vital role in the scientiﬁc community of evaluating the contributions of scientiﬁc authors. Citing sources delivers a measurable way of evaluating the impact factor of journals and authors and allows for the recognition of new research issues. Different techniques for classifying citations have been proposed. Citations that provide background knowledge in the citing document have been classified as non-important or incidental by previous researchers. Citations that extend previous work in the citing document are classified as important. The accuracy achieved by existing citation models is not much higher. Better features need to be included for accurate predictions. A hybrid approach would present all possible combinations of cue-words and in-text citation-based features for citation classiﬁcations.
关键词：Cue-words; in-text citation; hybrid