Intakosum, Sarun

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Intakosum, Sarun
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sarun.in@kmitl.ac.th

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    Item type:Publication,
    Adaptation of design pattern retrieval using CBR and FCA
    (2009-12-01)
    Muangon, Weenawadee
    ;
    Intakosum, Sarun
    Software developers currently find design patterns through search tools for solving software design problem. However, these search tools still have keywordsearch problem. In this paper, we introduce the elementary idea to improve the design pattern retrieval tool. We propose the combination of Case Based Reasoning (CBR) and Formal Concept Analysis (FCA). Because of CBR lead to the smart solution and FCA provides flexible way to maintain indexing in the case base. © 2009 IEEE.
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    Item type:Publication,
    From use cases to framelets for building application frameworks
    (2008-05-27)
    Intakosum, Sarun
    Framework-based software development has been proven a useful technique to develop an application. However, the development of a large application framework itself is considered complex. There are two major causes for this problem, the size of a framework and the vague framework requirements. The idea of framelet a small but complete framework, can be applied to solve the former. The Framelet-based Approach for Framework Development (FAFD) has been proposed to address the later. There are some improvements in term of use case requirements description to the approach after it was first presented. This paper aims to report such improvements as well as the ongoing researches on the FAFD. © 2008 IEEE.
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    Item type:Publication,
    Closed multidimensional sequential pattern mining
    (2006-11-14)
    Songram, Panida
    ;
    Boonjing, Veera
    ;
    Intakosum, Sarun
    We propose a new method, called closed multidimensional sequential pattern mining, for mining multidimensional sequential patterns. The new method is an integration of closed sequential pattern mining and closed itemset pattern mining. Based on this method, we show that (1) the number of complete closed multidimensional sequential patterns is not larger than the number of complete multidimensional sequential patterns (2) the set of complete closed multidimensional sequential patterns covers the complete resulting set of multidimensional sequential patterns. In addition, mining using closed itemset pattern mining on multidimensional information would mine only multidimensional information associated with mined closed sequential patterns, and mining using closed sequential pattern mining on sequences would mine only sequences associated with mined closed itemset patterns. © 2006 IEEE.