Text-based classification incoming maintenance requests to maintenance type
Classifying maintenance request is one of the important task in the large software system, yet often in large software system are not well classified. This is due to difficult in classifying by software maintainer. The categorization of maintenance type is effect on determine the corrective, adaptiv...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2010
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| Online Access: | http://psasir.upm.edu.my/id/eprint/67882/1/Text-based%20classification%20incoming%20maintenance%20requests%20to%20maintenance%20type.pdf |
| _version_ | 1825933418149445632 |
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| author | Mahmoodian, Naghmeh Abdullah, Rusli Azmi Murad, Masrah Azrifah |
| author_facet | Mahmoodian, Naghmeh Abdullah, Rusli Azmi Murad, Masrah Azrifah |
| author_sort | Mahmoodian, Naghmeh |
| collection | UPM |
| description | Classifying maintenance request is one of the important task in the large software system, yet often in large software system are not well classified. This is due to difficult in classifying by software maintainer. The categorization of maintenance type is effect on determine the corrective, adaptive, perfective, and preventive which are important to determine various quality factors of the system. In this paper we found that the requests for maintenance support could be classified correctly into corrective and adaptive. We used two different machine learning techniques alternatively Naïve Bayesian and Decision tree to classify issues into two type. Machine learning approach used the features that could be effective in increasing the accuracy of the system. We used 10-fold cross validation to evaluate the system performance. 1700 issues from shipment monitoring system were used to asses the accuracy of the system. |
| first_indexed | 2024-03-06T09:56:58Z |
| format | Conference or Workshop Item |
| id | upm.eprints-67882 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T09:56:58Z |
| publishDate | 2010 |
| publisher | IEEE |
| record_format | dspace |
| spelling | upm.eprints-678822019-06-12T07:35:38Z http://psasir.upm.edu.my/id/eprint/67882/ Text-based classification incoming maintenance requests to maintenance type Mahmoodian, Naghmeh Abdullah, Rusli Azmi Murad, Masrah Azrifah Classifying maintenance request is one of the important task in the large software system, yet often in large software system are not well classified. This is due to difficult in classifying by software maintainer. The categorization of maintenance type is effect on determine the corrective, adaptive, perfective, and preventive which are important to determine various quality factors of the system. In this paper we found that the requests for maintenance support could be classified correctly into corrective and adaptive. We used two different machine learning techniques alternatively Naïve Bayesian and Decision tree to classify issues into two type. Machine learning approach used the features that could be effective in increasing the accuracy of the system. We used 10-fold cross validation to evaluate the system performance. 1700 issues from shipment monitoring system were used to asses the accuracy of the system. IEEE 2010 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/67882/1/Text-based%20classification%20incoming%20maintenance%20requests%20to%20maintenance%20type.pdf Mahmoodian, Naghmeh and Abdullah, Rusli and Azmi Murad, Masrah Azrifah (2010) Text-based classification incoming maintenance requests to maintenance type. In: International Symposium on Information Technology (ITSim'10), 15-17 June 2010, Kuala Lumpur Convention Centre, Kuala Lumpur. (pp. 693-697). 10.1109/ITSIM.2010.5561540 |
| spellingShingle | Mahmoodian, Naghmeh Abdullah, Rusli Azmi Murad, Masrah Azrifah Text-based classification incoming maintenance requests to maintenance type |
| title | Text-based classification incoming maintenance requests to maintenance type |
| title_full | Text-based classification incoming maintenance requests to maintenance type |
| title_fullStr | Text-based classification incoming maintenance requests to maintenance type |
| title_full_unstemmed | Text-based classification incoming maintenance requests to maintenance type |
| title_short | Text-based classification incoming maintenance requests to maintenance type |
| title_sort | text based classification incoming maintenance requests to maintenance type |
| url | http://psasir.upm.edu.my/id/eprint/67882/1/Text-based%20classification%20incoming%20maintenance%20requests%20to%20maintenance%20type.pdf |
| work_keys_str_mv | AT mahmoodiannaghmeh textbasedclassificationincomingmaintenancerequeststomaintenancetype AT abdullahrusli textbasedclassificationincomingmaintenancerequeststomaintenancetype AT azmimuradmasrahazrifah textbasedclassificationincomingmaintenancerequeststomaintenancetype |