|
JAIST Repository >
School of Information Science >
Articles >
Journal Articles >
Please use this identifier to cite or link to this item:
https://hdl.handle.net/10119/14736
|
| Title: | A multi-objectives genetic algorithm clustering ensembles based approach to summarize relational data |
| Authors: | Alfred, Rayner
Chiye, Gabriel Jong
Lim, Yuto
On, Chin Kim
Obit, Joe Henry |
| Keywords: | Relational Data Mining
k-Means
Multi-objectives
Ensembles
Genetic Algorithm |
| Issue Date: | 2016-09-18 |
| Publisher: | Springer |
| Magazine name: | Communications in Computer and Information Science |
| Volume: | 652 |
| Start page: | 113 |
| End page: | 122 |
| DOI: | 10.1007/978-981-10-2777-2_10 |
| Abstract: | Dynamic Aggregation of Relational Attributes is one of the approaches which can be used to learn relational data. It is capable to transform a multi-relational database into a vector space representation. Traditional clustering algorithm can then be applied directly on the vector space representation to learn and summarize the relational data. However、 the performance of the algorithm is highly dependent on the quality of clusters produced. A small change in the initialization of the clustering algorithm parameters may cause adverse effects to the clusters quality produced. In order to optimize the quality of clusters、 a Genetic Algorithm is used to find the best combination of initializations and settings to produce the optimal clusters. The proposed method involves the task of finding the best initialization with respect to the number of clusters、 proximity distance measurements、 fitness functions、 and classifiers used for the evaluation. Based on the results obtained、 clustering coupled with Euclidean distance is found to perform better in the classification stage compared to using clustering coupled with Cosine similarity. Based on the findings、 the cluster entropy is the best fitness function、 followed by multi-objectives fitness function used in the genetic algorithm. This is most probably because of the involvement of external measurement that takes the class label into consideration in optimizing the structure of the cluster results. |
| Rights: | This is the author-created version of Springer, Rayner Alfred, Gabriel Jong Chiye, Yuto Lim, Chin Kim On, Joe Henry Obit, Communications in Computer and Information Science, 652, 2016, 113-122. The original publication is available at www.springerlink.com, http://dx.doi.org/10.1007/978-981-10-2777-2_10 |
| URI: | https://hdl.handle.net/10119/14736 |
| Material Type: | author |
| Appears in Collections: | b10-1. 雑誌掲載論文 (Journal Articles)
|
Files in This Item:
| File |
Description |
Size | Format |
|---|
| 22896.pdf | | 212Kb | Adobe PDF | View/Open |
|
All items in DSpace are protected by copyright, with all rights reserved.
|
