- Title
- Input data representation for self-organising map in software classification
- Creator
- Lin, Yuqing; Ye, Huilin
- Relation
- 2nd International Symposium on Knowledge Acquisition and Modeling, 2009 (KAM '09). Proceedings of the 2nd International Symposium on Knowledge Acquisition and Modeling 2009 (Huazhong Normal University, China 30 November - 1 December, 2009) p. 350-353
- Publisher Link
- http://dx.doi.org/10.1109/KAM.2009.151
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Resource Type
- conference paper
- Date
- 2009
- Description
- A self-organizing map (SOM) is used to classify software documents and the associated software components with the aim to facilitate software reuse. SOM learns from input stimuli rather than training data, therefore the quality of input data representation is crucial to the success of SOM. In this paper, we use automatic indexing method to represent a document collection as the input data to train a SOM. The automatic indexing uses a phrase formation method to promote precision and a domain dependent relational thesaurus to enhance recall. A retrieval experiment based on a document collection containing 97 Unix manual pages was conducted to evaluate the effectiveness of this input data representation scheme. Promising retrieval results were observed.
- Subject
- self-organizing map; automatic indexing; software classification; input data representation; Unix manual pages
- Identifier
- uon:8767
- Identifier
- http://hdl.handle.net/1959.13/919051
- Identifier
- ISBN:9780769538884
- Rights
- Copyright © 2009 IEEE. Reprinted from the Proceedings of the 2nd International Symposium on Knowledge Acquisition and Modeling 2009. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of University of Newcastle's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
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