An improved self organizing map using jaccard new measure for textual bugs data clustering
In software projects there is a data repository which contains the bug reports. These bugs are required to carefully analyze to resolve the problem. Handling these bugs humanly is extremely time consuming process, and it can result the delaying in addressing some important bugs resolutions. To overc...
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| Format: | Thesis |
| Language: | English English English |
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2018
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| Online Access: | http://eprints.uthm.edu.my/7554/ http://eprints.uthm.edu.my/7554/1/24p%20ATTIKA%20AHMED.pdf http://eprints.uthm.edu.my/7554/2/ATTIKA%20AHMED%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/7554/3/ATTIKA%20AHMED%20WATERMARK.pdf |
| _version_ | 1848889136962863104 |
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| author | Ahmed, Attika |
| author_facet | Ahmed, Attika |
| author_sort | Ahmed, Attika |
| building | UTHM Institutional Repository |
| collection | Online Access |
| description | In software projects there is a data repository which contains the bug reports. These bugs are required to carefully analyze to resolve the problem. Handling these bugs humanly is extremely time consuming process, and it can result the delaying in addressing some important bugs resolutions. To overcome this problem researchers have been introduced many techniques. One of the techniques is the bug clustering. For the purpose of clustering, a variety of clustering algorithms available. One of the commonly used algorithm for bug clustering is K-means, which is considered a simplest unsupervised learning algorithm for clustering, yet it tends to produce smaller number of cluster. Considering the unsupervised learning algorithms, SelfOrganizing Map (SOM) considers the equally compatible algorithm for clustering, as both algorithms are closely related but different in way they were used in data mining. This research attempts a comparative analysis of both the clustering algorithms and for attaining the results, a series of experiment has been conducted using Mozilla bugs data set. To address the data sparseness issue, the experiment has been perfonned on textual bugs' data by using two different distance measure which are Euclidean distance and Jaccard New Measure. The research results suggested that SOM has a limitation of poor perfonnance on sparse data set. Thus, the research introduced the improved SOM algorithm by using a Jaccard NM (SOM-JNM). The SOM-JNM produced significantly better results therefore; it can be consider a challenging approach to address the sparse data problems. |
| first_indexed | 2025-11-15T20:21:23Z |
| format | Thesis |
| id | uthm-7554 |
| institution | Universiti Tun Hussein Onn Malaysia |
| institution_category | Local University |
| language | English English English |
| last_indexed | 2025-11-15T20:21:23Z |
| publishDate | 2018 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uthm-75542022-08-21T01:45:13Z http://eprints.uthm.edu.my/7554/ An improved self organizing map using jaccard new measure for textual bugs data clustering Ahmed, Attika QA Mathematics QA1-43 General In software projects there is a data repository which contains the bug reports. These bugs are required to carefully analyze to resolve the problem. Handling these bugs humanly is extremely time consuming process, and it can result the delaying in addressing some important bugs resolutions. To overcome this problem researchers have been introduced many techniques. One of the techniques is the bug clustering. For the purpose of clustering, a variety of clustering algorithms available. One of the commonly used algorithm for bug clustering is K-means, which is considered a simplest unsupervised learning algorithm for clustering, yet it tends to produce smaller number of cluster. Considering the unsupervised learning algorithms, SelfOrganizing Map (SOM) considers the equally compatible algorithm for clustering, as both algorithms are closely related but different in way they were used in data mining. This research attempts a comparative analysis of both the clustering algorithms and for attaining the results, a series of experiment has been conducted using Mozilla bugs data set. To address the data sparseness issue, the experiment has been perfonned on textual bugs' data by using two different distance measure which are Euclidean distance and Jaccard New Measure. The research results suggested that SOM has a limitation of poor perfonnance on sparse data set. Thus, the research introduced the improved SOM algorithm by using a Jaccard NM (SOM-JNM). The SOM-JNM produced significantly better results therefore; it can be consider a challenging approach to address the sparse data problems. 2018-01 Thesis NonPeerReviewed text en http://eprints.uthm.edu.my/7554/1/24p%20ATTIKA%20AHMED.pdf text en http://eprints.uthm.edu.my/7554/2/ATTIKA%20AHMED%20COPYRIGHT%20DECLARATION.pdf text en http://eprints.uthm.edu.my/7554/3/ATTIKA%20AHMED%20WATERMARK.pdf Ahmed, Attika (2018) An improved self organizing map using jaccard new measure for textual bugs data clustering. Masters thesis, Universiti Tun Hussein Onn Malaysia. |
| spellingShingle | QA Mathematics QA1-43 General Ahmed, Attika An improved self organizing map using jaccard new measure for textual bugs data clustering |
| title | An improved self organizing map using jaccard new measure for textual bugs data clustering |
| title_full | An improved self organizing map using jaccard new measure for textual bugs data clustering |
| title_fullStr | An improved self organizing map using jaccard new measure for textual bugs data clustering |
| title_full_unstemmed | An improved self organizing map using jaccard new measure for textual bugs data clustering |
| title_short | An improved self organizing map using jaccard new measure for textual bugs data clustering |
| title_sort | improved self organizing map using jaccard new measure for textual bugs data clustering |
| topic | QA Mathematics QA1-43 General |
| url | http://eprints.uthm.edu.my/7554/ http://eprints.uthm.edu.my/7554/1/24p%20ATTIKA%20AHMED.pdf http://eprints.uthm.edu.my/7554/2/ATTIKA%20AHMED%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/7554/3/ATTIKA%20AHMED%20WATERMARK.pdf |