2024-03-28T13:05:19Z
https://meral.edu.mm/oai
oai:meral.edu.mm:recid/5010
2022-03-24T23:14:08Z
1582963302567:1597824273898
user-ucsy
Searching Suitable Employee for the Work by Using Partitioning Methods
Nwe, Win Hay Mar
Kham, Nang Saing Moon
Conventional database query methods areinadequate to extract useful information from hugedata banks. Cluster analysis is one of the major dataanalysis methods, and process of grouping a set ofphysical or abstract objects into classes of similarobjects. A cluster is the collection of data objects thatare similar to one another within the same clusterand are dissimilar to the objects in other clusters.There are many approaches for clustering method.Partitioning is the well-known and efficientalgorithm and K-Mean is the partitioning methodand widely used in many applications. In this paper,K-means clustering method is used to find theappropriate employee from many job seekers andgive that information to the employer to choose fortheir work. The k-means clustering methods aredetermining level of employee based on theirprofiles. Thus, many companies are easy to findappropriate employee for their work.
2010-12-16
http://hdl.handle.net/20.500.12678/0000005010
https://meral.edu.mm/records/5010