Classification of research papers using citation links and citation types: Towards automatic review article generation.

Abstract

We are investigating automatic generation of a review (or survey) article in a specific subject domain. In a research paper, there are passages where the author describes the essence of a cited paper and the differences between the current paper and the cited paper (we call them citing areas). These passages can be considered as a kind of summary of the cited paper from the current author's viewpoint. We can know the state of the art in a specific subject domain from the collection of citing areas. Further, if these citing areas are properly classified and organized, they can act as a kind of a review article. In our previous research, we proposed the automatic extraction of citing areas. Then, with the information in the citing areas, we automatically identified the types of citation relationships that indicate the reasons for citation (we call them citation types). Citation types offer a useful clue for organizing citing areas. In addition, to support writing a review article, it is necessary to take account of the contents of the papers together with the citation links and citation types. In this paper, we propose several methods for classifying papers automatically. We found that our proposed methods BCCT-C, the bibliographic coupling considering only type C citations, which pointed out the problems or gaps in related works, are more effective than others. We also implemented a prototype system to support writing a review article, which is based on our proposed method.

Citation Block Determination Using Textual Coherence

“…References [44], [45] present a similar task of finding "related sentences" to a citation anchor; they use a set of 90 cue-phrases extracted from a set of 100 citation blocks with a simple-matching * 18 Even this one is likely coincidental, as it ("meanwhile") had only a single positive example and no negative examples in the data.…”

“…There is a wealth of research from over the decades focusing on citations and citation analysis in various forms; this includes citation network analysis, like indexes [16], [18], bibliographic coupling [29], co-citation [56], citation counts [68], and the hindex [24], analysis of citation role/function [60], [67], analysis of sociological aspects [70], domain summarisation [15], [17], [44], [50], [52], paper summarisation [27], [51], and sentiment analysis [1], [43].…”

Analysis of Research status based on Citation Context

“…This analysis is based on 1) the evaluation by paper, journal and researcher of research output, 2) the identification of emerging research topics, 3) the production of the map for the intellectual structure analysis by research domain and 4) various services for academic information [9,10,15,16] [11], [18], [28]. Furthermore, research on citation summarization and visualization based on both citation context and citation function of citations has been tried.…”

A Rule-based Approach to Identifying Citation Text from Korean Academic Literature

“…, 리뷰 논문 자동 생성 (Nanba, Kando, & Okumura, 2000), 인용문 감성 분석 (Athar & Teufel, 2012), 인용문 기반 문헌 검색 (O'Connor, 1982;Bradshaw, 2003;Ritchie, Robertson, & Teufel, 2008 •원 규칙: •FP-3: 이러한 카테고리를 고려하여 Wang …”