Rules extraction based on data summarisation approach using DARA

Rayner Alfred (2008) Rules extraction based on data summarisation approach using DARA. In: 4th International Conference on Advanced Data Mining and Applications (ADMA 2008), 8-10 October 2008, Chengdu, China.

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This paper helps the understanding and development of a data summarisation approach that summarises structured data stored in a non-target table that has many-to-one relations with the target table. In this paper, the feasibility of data summarisation techniques, borrowed from the Information Retrieval Theory, to summarise patterns obtained from data stored across multiple tables with one-to-many relations is demonstrated. The paper describes the Dynamic Aggregation of Relational Attributes (DARA) framework, which summarises data stored in non-target tables in order to facilitate data modelling efforts in a multi-relational setting. The application of the DARA algorithm involving structured data is presented in order to show the adaptability of this algorithm to real world problems. © 2008 Springer-Verlag Berlin Heidelberg.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Uncontrolled Keywords: Data modelling, Dynamic aggregation, Information retrieval theory, Many-to-one, Real-world problem, Rules extraction, Structured data
Subjects: ?? QA75-76.95 ??
Divisions: SCHOOL > School of Engineering and Information Technology
Depositing User: ADMIN ADMIN
Date Deposited: 24 Mar 2011 06:01
Last Modified: 30 Dec 2014 06:59

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