A new method for classifying and searching software components by using a self-organizing neural network architecture

被引：0
|
作者：
Mello, Claudia A. S. [1 ]
de Mello, Rodrigo F. [2 ]
Santos, Marilde T. P. [1 ]
Senger, Luciano J. [3 ]
Yang, Laurence T. [4 ]
机构：
[1] Univ Fed Sao Carlos, Dept Computacao, Rod Washington Luis Km 235, BR-13560970 Sao Carlos, SP, Brazil
[2] Univ Sao Paulo, Inst Ciencia Matemat, BR-1356070 Sao Carlos, SP, Brazil
[3] Univ Estadual Ponta Grossa, Dept Informat, Ponta Grossa, PR, Brazil
[4] Xavier Univ, Antigonish, NS, Canada
来源：
2006 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING | 2006年
关键词：
software component repositories; search strategy; neural networks;
D O I：
10.1109/GRC.2006.1635772
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The method presented in this paper aims to simplify the construction of software component repositories. The repository makes possible the reuse of components, reducing the software implementation costs. The proposed method extracts informations from component documentation, or either, terms which compound the metadata to represent components. The components are automatically grouped, using the terms, in the repository by means of the ART-2A self-organizing artificial neural network architecture. The vectorial search strategy is used to retrieve software components which are grouped by the neural network. Experiments showed that this strategy improved the ordinary vectorial search by an average of 9.55% in precision, maintaining a similar quality in recall. This method also presented an relevant increase in the search performance.
引用
收藏
页码：136 / +
页数：2
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