형식개념분석기법을 이용한 사용자 질의 기반의 연관관계 추출 자동화지원도구의 개발
On Development of an Automatic Tool for Extracting Association Rules of a user query using Formal Concept Analysis
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Formal Concept Analysis (FCA) is a widely used methodology for data analysis, which extracts concepts and builds a concept hierarchy from given data. A concept consists of objects and attributes shared by those objects, and a concept hierarchy includes information on super-sub relations among the concepts. In this paper, we propose a method for extracting Implication and Association rules from a concept hierarchy given a query by a user. The method also describes a way for displaying the extracted rules. Based on this method, we implemented an automatic tool, QAG-Wizard. Because the QAG-Wizard not only elicits relation information for the given query, but also displays it in structured form intuitively, we expect that it can be used in the fields of data analysis, data mining and information retrieval for various purposes.
Abstract
Formal Concept Analysis (FCA) is a widely used methodology for data analysis, which extracts concepts and builds a concept hierarchy from given data. A concept consists of objects and attributes shared by those objects, and a concept hierarchy includes information on super-sub relations among the concepts. In this paper, we propose a method for extracting Implication and Association rules from a concept hierarchy given a query by a user. The method also describes a way for displaying the extracted rules. Based on this method, we implemented an automatic tool, QAG-Wizard. Because the QAG-Wizard not only elicits relation information for the given query, but also displays it in structured form intuitively, we expect that it can be used in the fields of data analysis, data mining and information retrieval for various purposes.
참고문헌 (14)
- B. Ganter, "Formal Concept Analysis Mathematical Foundations" (1999), Springer-Verlag
- C. Carpineto, "Concept Data Analysis, Theory and Applications" (2004), Wiley
- Nicolas Pasquier, "Efficient mining of association rules using closed itemset lattices", Information Systems, 24(1), pp.25~46 (1999)
- Nicolas Pasquier, "Discovering Frequent Closed Itemsets for Association Rules", Lecture Notes in Computer Science, 1540, pp.398~416 (1999)
- Keyun Hu, "Integrating Classification and Association Rule Mining: A Concept Lattice Framework", Lecture Notes in Computer Science, 1711, pp.443~447 (2004)
- Gerd Stumme, "Intelligent structuring and Reducing of Association Rules with Formal Concept Analysis", Lecture Notes in Computer Science, 2174, pp.335~350 (2001)
- "Concept Explorer"[URL]
- "Galicia"[URL]
- "Toscana J"[URL]
- Yo-Ping Huang, "Using Association Rules for Expanding Search Engine Recommendation Keywords in English and Chinese for Search Engine Queries", the 8th IASTED International Conference on Intelligent Systems and Control ISC 2005, pp.465~470 (2005)
- Peter Bodík, "Advanced Tools for Operators at Amazon.com", First Workshop on Hot Topics in Autonomic Computing (HotAC’06) (2006)
- "JPowerGraph"[URL]
- "JTree"[URL]
- "JTable"[URL]
