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  • P-ISSN1013-0799
  • E-ISSN2586-2073
  • KCI

A Study on Developing a Metadata Search System Based on the Text Structure of Korean Studies Research Articles

Journal of the Korean Society for Information Management / Journal of the Korean Society for Information Management, (P)1013-0799; (E)2586-2073
2016, v.33 no.3, pp.155-176
https://doi.org/10.3743/KOSIM.2016.33.3.155



Abstract

This study aims to develope a scholarly metadata information system based on conceptual elements of text structure of Korean studies research articles and to identify the applicability of text structure based metadata as compared with the existing similar system. For the study, we constructed a database(Korean Studies Metadata Database, KMD) with text structure based on metadata of Korean Studies journal articles selected from the Korea Citation Index(KCI). Then we verified differences between KCI system and KMD system through search results using same keywords. As a result, KMD system shows the search results which meet the users’ intention of searching more efficiently in comparison with the KCI system. In other words, even if keyword combinations and conditional expressions of searching execution are same, KMD system can directly present the content of research purposes, research data, and spatial-temporal contexts of research et cetera as search results through the search procedure.

keywords
한국학, 연구 논문, 텍스트 구조, 의미 구조, 메타데이터 검색 시스템, Korean studies, research articles, text structure, semantic structure, metadata search system

Reference

1.

고영만. (2011). 연구문헌의 지식구조를 반영하는 의미기반의 지식조직체계에 관한 연구. 정보관리학회지, 28(1), 145-170.

2.

박진용. (1997). 텍스트 의미구조의 과정 중심 분석 방법 연구.

3.

송민선. (2015). 한국학 연구 논문의 의미 구조 기반 메타데이터 연구. 한국도서관·정보학회지, 46(3), 277-299.

4.

유사라. (2009). 연구자 중심 연구성과물 의미검색을 위한 인문사회 학술용어 온톨로지 적용 및 유지관리 체계 연구. 한국문헌정보학회지, 43(2), 277-298.

5.

정여훈. (2013). 수사구조이론과 한국어 텍스트 분석의 실제. 언어사실과 관점, 32, 261-288.

6.

Beissel-Durrant, G.. (2004). A typology of research methods within the social sciences. National Centre for Research Methods.

7.

Bouayad-Agha, N.. (2000). Can text structure be incompatible with rhetorical structure? (12-16). Proceedings of the First International Conference on Natural Language Generation.

8.

Brewer, W. F.. (1980). Theoretical issues in reading comprehension:Perspectives from cognitive psychology, linguistics, artificial intelligence, and education:Lawrence Erlbaum Associates.

9.

Brinker, K.. (1985). Linguistische textanalyse:Erich Schmitdt Verlag.

10.

Buckingham Shum, S.. (2000). Scholonto: Ontology-based digital library server for research document and discourse. International Journal on Digital Libraries, 3, 237-248. http://dx.doi.org/10.1007/s007990000034.

11.

de Beaugrande, R.. (1981). Einführung in die textlinguistik:Niemeyer.

12.

Frederiksen, C. H.. (1975). Representing logical and semantic structure of knowledge acquired from discourse. Cognitive Psychology, 7(3), 371-458. http://dx.doi.org/10.1016/0010-0285(75)90016-x.

13.

Halladay, M. A. K.. (1976). Cohension in English:Longman.

14.

Harmsze, F. A. P.. (2000). A modular structure for scientific articles in an electronic environment.

15.

Heflin, J.. (1998). Reading between the lines: Using SHOE to discover implicit knowledge from the web (-). AAAI-98 Workshop on AI and Information Integration.

16.

Kampa, S. R.. (2002). Who are the expert? e-scholars in the semantic web.

17.

Kando, N.. (1997). Text-level structure of research papers: Implications for text-based information processing systems (68-81). Proceedings of the 19th Annual BCS-IRSG Colloquium on IR Research.

18.

Kando, N.. (1999). Text structure analysis as a tool to make retrieved documents sable (126-135). Proceedings of the 4th International Workshop on Information Retrieval with Asian Languages.

19.

Kintsch, W.. (1974). The representation of meaning in memory:Lawrence Erlbaum.

20.

Luke, S.. (1996). Ontology-based knowledge discovery on the worldwide web (96-102). Working Notes of the Workshop on Internet-Based Information Systems at the 13th National Conference on Artificial Intelligence (AAAI96).

21.

Meyer, B. J. F.. (1975). The organization of prose and its effects on memory:North-Holland Publishing Co.

22.

Ono, K.. (1994). Abstract generation based on rhetorical structure extraction (344-348). Proceedings of the 15th conference on Computational linguistics.

23.

Shotton, D.. (2009). Cito, the citation typing ontology. Journal of Biomedical Semantics, 1(Suppl 1), S6-. http://dx.doi.org/10.1186/2041-1480-1-s1-s6.

24.

Sibun, P.. (1993). Domain structure, rhetorical structure, and text structure (-). Proceedings of the Workshop on Intentionality and Structure in Discourse Relations on the 31st ACL. Ohio State University Columbus.

25.

Superceanu R.. (1998). The rhetoric of scientific articles: A genre study:Orizonturi Universitare.

26.

van Dijk, T. A.. (1980). Macrostructures: An interdisciplinary study of global structures in discourse, interaction, and cognition:Lawrence Erlbaum.

27.

Vater, H.. (1994). Einführung in die textlinguistik:Wilhelm Fink Verlag.

28.

Weigand, E.. (2009). Language as dialogue: From rules to principles of probability:John Benjamins Publishing Company.

29.

Werlich, E.. (1976). A text grammar of English:Quelle und Meyer.

Journal of the Korean Society for Information Management