OCCT: A One –Class Clustering Tree for Implementing One – to- Many and Many – to- Many Data Linkage
Author(s) -
Manali Pare,
Anju Singh,
Divaker Singh
Publication year - 2016
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2016908522
Subject(s) - computer science , cluster analysis , linkage (software) , class (philosophy) , tree (set theory) , data mining , data science , information retrieval , machine learning , artificial intelligence , mathematics , mathematical analysis , biochemistry , chemistry , gene
One to many & many to many data linkage are necessary in data mining. OCCT Implementation for one to many & Many to many Data Linkage is to identify different entities across different Data sources. Data Linkage is linking data between two different database. One to many data linkage is associated an entity from first data set with a group matching from the other data set. In many to Many Data Linkage method the entities of same type and different nature should be arrange with Map Reduce method. In the OCCT was evaluated after using data sets from three different domains: , recommender system, data leakage prevention and fraud detection. data leakage prevention domain, the goal is to detect abnormal access. Recommender system, the method is used for matching new users of the system with the items. In fraud detection legitimate transactions performed by users.
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