A Study on the Frequency Level Preference Tendency of Association Measures (연관성 척도의 빈도수준 선호경향에 대한 연구)

Lee, Jae Yun (이재윤)

doi:10.3743/KOSIM.2004.21.4.281

A Study on the Frequency Level Preference Tendency of Association Measures

Journal of the Korean Society for Information Management
Abbr : JKOSIM
2004, 21(4), pp.281~294
DOI : 10.3743/KOSIM.2004.21.4.281
Publisher : 한국정보관리학회
Research Area : Interdisciplinary Studies > Library and Information Science
Received : November 19, 2004
Accepted : December 13, 2004
Published : December 30, 2004

Lee, Jae Yun ¹

¹경기대학교

Accredited

ABSTRACT

Association measures are applied to various applications, including information retrieval and data mining. Each association measure is subject to a close examination to its tendency to prefer high or low frequency level because it has a significant impact on the performance of applications. This paper examines the frequency level preference(FLP) tendency of some popular association measures using artificially generated cooccurrence data, and evaluates the results. After that, a method of how to adjust the FLP tendency of major association measures such as cosine coefficient is proposed. This method is tested on the cooccurrence-based query expansion in information retrieval and the result can be regarded as promising the usefulness of the method. Based on these results of analysis and experiment, implications for related disciplines are identified.

KEYWORDS

Association Measures, Cooccurrence Analysis, Information Retrieval, Data Mining

Citation status

* References for papers published after 2023 are currently being built.

[confproc] 김지영 / 2000 / 한국어 테스트 컬렉션 HANTEC의 확장 및 보완 / 제12회 한글 및 한국어 정보치리 학술대회 논문집 : 210~215

[book] 사공철 / 2003 / 정보학 사전 / 서울: 문헌정보처리연구회

[journal] 이재윤 / 2003 / 상호정보량의 정규화에 대한 연구 / 문헌정보학회지 37(4) : 177~198

[book] 정영미 / 1987 / 정보검색론 / 서울: 정음사

[journal] Chung, Young Mee / 2001 / A corpus-based approach to comparative evaluation of statistical term association measures / Journal of the American Society for Information Science and Technology 352(4) : 283~296

[journal] Chung, Young Mee / 2004 / Optimization of some factors affecting the performance of query expansion / Information Processing and Management 40(6) : 891~917

[journal] Forman, George / 2003 / An extensive empirical study of feature selection metrics for text classification / Journal of Machine Learning Research 3 : 1289~1305

[confproc] Galavotti, L / 2000 / Experiments on the use of feature selection and negative evidence in automated text categorization / Proceedings of ECDL- 00, 4th European Conference on Research and Advanced Technology for Digital Libraries(Lisbon, Portugal, 2000) : 59~68

[book] Gower, J. C / 1985 / Measures of similarity, dissimilarity, and distance(In Encyclopedia of Statistical Sciences, Vol. 5) : 397~405

[journal] Meyer, A / 2004 / Comparison of similarity coefficients used for cluster analysis with dominant markers in maize (Zea mays L) / Genetics and Molecular Biology 27(1) : 83~91

[confproc] Mladeni'c, D / 1998 / Feature subset selection in text-learning / In Proceedings of the Tenth European Conference on Machine Learning(Chemnitz, Germany, 1998) : 95~100

[journal] Salton, G / 1973 / On the specification of term values in automatic indexing / Journal of Documentation 29(4) : 351~372

[book] van Rijsbergen, C. J / 1979 / Information Retrieval. 2nd ed. / London: Butterworths

[confproc] Yang, Yiming / 1997 / A comparative study on feature selection in text categorization / Proceedings of the 14th International Conference on Machine Learning : 412~420

KJCKorea
Journal Central

Journal of the Korean Society for Information Management 2023 KCI Impact Factor : 1.31

A Study on the Frequency Level Preference Tendency of Association Measures

ABSTRACT

KEYWORDS

Citation status

* References for papers published after 2023 are currently being built.

Journal of the Korean Society for Information Management 2023 KCI Impact Factor : 1.31

A Study on the Frequency Level Preference Tendency of Association Measures

ABSTRACT

KEYWORDS

Statistics

Tools

Issue List

Citation status

KCI Citation Counts (3)

REFERENCES (14) * References for papers published after 2023 are currently being built.

Search PDF

Citation

* References for papers published after 2023 are currently being built.