A Survey On One Class Clustering Tree For One To Many Data Linkage |
Author(s): |
| Kalyani Ravindra Mandilkar , Amrutvahini college of enggineering |
Keywords: |
| Clustering, Data Linkage, OCCT, Splitting Criteria, Purning Methods |
Abstract |
|
Data linkages is to identify different entities across different data sources. There are two types of data linkages techniques as One to One and One to Many data linkages. One to many data linkage technique that links between entities of different nature. The method proposed is based on a one class clustering tree (OCCT). The OCCT is built in such a way that it is easy to understand and can be convert into the association rules. The inner nodes of the tree consist of features describing the first set of entities and the leaves of the tree describes features of their matching entities from second data. In this paper we are using four splitting and two purning methods. The result shows that OCCT gives better performances in terms of precision and recall when compared to C4.5 decision tree linkage method. |
Other Details |
|
Paper ID: IJSRDV5I110103 Published in: Volume : 5, Issue : 11 Publication Date: 01/02/2018 Page(s): 214-216 |
Article Preview |
|
|
|
|
