| Author | Tai, Xin |
| Call Number | AIT Thesis no. CS-00-34 |
| Subject(s) | Data mining
|
| Note | A Thesis submitted in partial fulfillment of the requirements for the degree of Master of Science, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis ; no. CS-00-34 |
| Abstract | Data clustering is regarded as a particular branch of data mining. In this thesis, data clustering refers to the problem of dividing N data points into K groups to minimize the intra.group difference, such as the sum of the squared distances from the cluster centers. In this thesis study, I deal with the important characteristics of clustering in spatial knowledge discovery. In this approach, I studied various data clustering methods, and analyze properties and features of the data clusters in spatial data sets. And, on the basis of the existing methods of B-tree, R-tree and R *-tree in spatial data mining, I built up an efficient and smart Clustering Feature Entry R-tree that is an improvement over an R-tree method. The CFE R-tree reduces the problem of clustering the original data points into a simpler and smaller one of clustering the clustered sub-clusters. And, experimentally, I also use some spatial data sets to implement the data clustering searching by using the modified CFE R-tree. |
| Year | 2000 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis ; no. CS-00-34 |
| Type | Thesis |
| School | School of Advanced Technologies (SAT) |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Computer Science (CS) |
| Chairperson(s) | Sadananda, Ramakoti; |
| Examination Committee(s) | Qi, Yulu;Afzulpurkar, Nitin V.; |
| Scholarship Donor(s) | State Education Council, P.R. China; |
| Degree | Thesis (M.Sc.) - Asian Institute of Technology, 2000 |