Mas Based Framework for Recruitment of Fresher’s By CMM Level Company
Journal Title: INTERNATIONAL JOURNAL OF COMPUTER TRENDS & TECHNOLOGY - Year 2014, Vol 9, Issue 5
Abstract
Every company has to hire freshers for its business process the hiring process involves time and cost of company this costing increase when in a particular drive company does not get appropriate candidates for hiring. The problem is every time company’s HR visits a college they only have a list of eligible candidates based on percentage and backlogs. This list gives an overview of the college it is quite possible the eligible students are not appropriate to be hired for working in the company. The proposed work is solution to the problem by using a framework of multiagent system, this framework consists of various agents which have their own specific task. However, a single agent cannot perform all the complex activities so we are using distributed problem solving approach and use various agents to perform different activities of the framework. Each agent has a fixed task and activity. In addition, agents involved in a multiagent system have the capability to interact, communicate, collaborate and share knowledge. With these properties, our agents solve the complex task of the problem. In proposed system company request for hiring freshers also gives its parameters. Proposed system involves various agents to select region, state and college based on parameters of the request of company these agents work according to their task and provide a list of appropriate candidates.
Authors and Affiliations
Alankar Srivastava , Ramesh Vaishya
Keywords
Related Articles
- EP ID EP152388
- DOI -
- Views 114
- Downloads 0
Effect of Principle Component Analysis and Support Vector Machine in Software Fault Prediction
Machine Learning (ML) approaches have a great impact in fault prediction. Demand for producing quality assured software in an organization has been rapidly increased during the last few years. This leads to increase in d...
Harmony Search Optimization in K-Means Clustering
Clustering is a data mining technique that classifies a set of observations into clusters based on some similarity measures. The most commonly used partitioning based clustering algorithm is K-means. However, the K-means...
Enhance the XML Documents Security using Web Services
An increasing amount of semi-structured data, XML has become fundamental to humans and programs. XML changed by the World Wide Web Consortium (w3c) is quickly emerging as a new standard language for semi-structured data...
Image Search Reranking
The existing methods for image search re ranking suffer from the unfaithfulness of the as sumptions under which the text-based images search result. The resulting images contain more irrelevant images. Hence the re ranki...
Depth Sensor Based Skeletal Tracking Evaluation for Fall Detection Systems
Falls are very common in elderly due to various physical constraints. Since falls may cause serious injury and even death, fall detection systems are very important, especially when the victim is alone at home or is unab...