Searching Suitable Employee for the Work by Using Partitioning Methods

Abstract

Conventional database query methods are inadequate to extract useful information from huge data banks. Cluster analysis is one of the major data analysis methods, and process of grouping a set of physical or abstract objects into classes of similar objects. A cluster is the collection of data objects that are similar to one another within the same cluster and are dissimilar to the objects in other clusters. There are many approaches for clustering method. Partitioning is the well-known and efficient algorithm and K-Mean is the partitioning method and widely used in many applications. In this paper, K-means clustering method is used to find the appropriate employee from many job seekers and give that information to the employer to choose for their work. The k-means clustering methods are determining level of employee based on their profiles. Thus, many companies are easy to find appropriate employee for their work.