The 2006 IEEE International Joint Conference on Neural Network Proceedings
DOI: 10.1109/ijcnn.2006.1716663
|View full text |Cite
|
Sign up to set email alerts
|

Fuzzy Clustering of Open-Source Software Quality Data: A Case Study of Mozilla

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
4
0

Publication Types

Select...
3
1
1

Relationship

0
5

Authors

Journals

citations
Cited by 5 publications
(4 citation statements)
references
References 0 publications
0
4
0
Order By: Relevance
“…OSPs begins with a developer/organizer setting the vision or the goal of the project and creating the architecture design for the project and preparing the project before opening up to the public [2,14,17]. Also, on the contribution of the members, it was suggested in the literature that members of open source communities contribute to OSP by efforts which included adding new features, improving old ones, updating, maintenance work and advertising OSP [7].…”
Section: Losc and Ospmentioning
confidence: 99%
See 1 more Smart Citation
“…OSPs begins with a developer/organizer setting the vision or the goal of the project and creating the architecture design for the project and preparing the project before opening up to the public [2,14,17]. Also, on the contribution of the members, it was suggested in the literature that members of open source communities contribute to OSP by efforts which included adding new features, improving old ones, updating, maintenance work and advertising OSP [7].…”
Section: Losc and Ospmentioning
confidence: 99%
“…Examples of famous OSPs include Mozilla Firefox and Linux Ubuntu [7,14]. Even though open source organizations depend on ultra-distribution, it was observed that many organizations depend on the efforts of local communities that meet face to face to work on OSPs.…”
Section: Introductionmentioning
confidence: 99%
“…Another paper that studies fuzzy clustering without prototypes is by Borgelt (Dick and Sadia [21]). An iterative update rule is derived from an objective function that only involves the proximities between data points and the membership degrees of the data points in the various clusters.…”
Section: Previous Work In Relational Clusteringmentioning
confidence: 99%
“…Table 7 Proximity matrix 3. 0, 2, 3, 6, 3, 6, 2, 2, 8,1,4,5,13,12,15,11,18,13,14,16,18,16,12,13,21,24,22,25,22,23,26,24,25,28,27,22 2, 0, 2, 2, 2, 5, 2, 5, 1, 8, 7, 4, 14, 17, 18, 16, 13, 13, 14, 10, 12, 14, 12, 17, 26, 24, 24, 28, 26, 24, 23, 26, 24, 28, 25, 21 3, 2, 0, 2, 4, 7, 5, 1, 5, 4, 5, 0, 14, 18, 11, 12, 15, 15, 14, 13, 13, 18, 16, 13, 25, 26, 26, 23, 22, 25, 25, 24, 25, 23, 25, 23 6, 2, 2, 0, 3, 1, 1, 5, 6, 2, 5, 4, 15, 15, 14, 17, 17, 17, 15, 15, 14, 14, 14, 15, 27, 24, 23, 21, 27, 24, 27, 22, 27, 22, 26, 27 3, 2, 4, 3, 0, 5, 7, 7, 1, 4, 1, 4, 13, 11, 15, 14, 15, 10, 16, 13, 10, 14, 14, 13, 28, 25, 22, 23, 23, 27, 24, 21, 26, 23, 27, 26 6, 5, 7, 1, 5, 0, 4, 2, 4, 3, 5, 6, 17, 16, 14, 14, 16, 12, 14, 16, 10, 14, 12, 11, 25, 23, 25, 24, 24, 25, 24, 24, 25, 23, 25, 20 2, 2, 5, 1, 7, 4, 0, 4, 2, 3, 2, 1, 14, 19, 12, 17, 14, 17, 14, 14, 11, 15, 14, 14, 21, 26, 24, 24, 22, 21, 27, 21, 24, 22, 25, 23 2, 5, 1, 5, 7, 2, 4, 0, 3, 1, 8, 6, 12, 13, 13, 11, 15, 13, 14, 13, 15, 15, 13, 12, 24, 20, 24, 25, 26, 20, 24, 27, 26, 21, 24, 26 8, 1, 5, 6, 1, 4, 2, 3, 0, 7, 5, 3, 14, 12, 14, 10, 16, 15, 10, 14, 11, 17, 15, 14, 26, 22, 21, 28, 23, 23, 24, 24, 26, 25, 23, 26 1, 8, 4, 2, 4, 3, 3, 1, 7, 0, 6, 4, 14, 14, 13, 16, 12, 11, 12, 14, 13, 14, 14, 16, 24, 22, 23, 28, 22, 22, 22, 22, 26, 24, 23, 23 4, 7, 5, 5, 1, 5, 2, 8, 5, 6, 0, 4, 14, 14, 13, 13, 11, 11, 14, 16, 10, 18, 13, 15, 23, 23, 21, 24, 27, 27, 20, 22, 26,...…”
Section: Simulation 4-obtaining Averages For the Cluster(ing) Qualitymentioning
confidence: 99%