DISCOVERY AND ANALYSIS OF JOB ELIGIBILITY AS ASSOCIATION RULES BY APRIORI ALGORITHM

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Published: Apr 20, 2018
DOI: https://doi.org/10.26483/ijarcs.v9i2.5650
Keywords:
Data mining, big data, association rule, support, confidence, classification, employment analytic

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Pankaj Kumar Deva Sarma
Department of Computer Science, Assam University, SILCHAR, ASSAM PIN 788 011

Abstract

Association rule mining is a data mining technique in which pattern of occurrences of one set of items with another set of items in databases of transactions are discovered as rules of implication with certain measures of interestingness. Support or the frequency of occurrences of sets of items and confidence are the most widely used measures of interestingness of association rules of the form X→Y where X and Y are disjoint sets of items. Though the problem of association rule mining emerged from analysis of market basket data in supermarket there are numerous areas of applications of association rule mining technique. In this paper, association rule mining method is applied to discover and analyze eligibility criteria for jobs from a large set of data for choosing career and professional goals effectively. For this the data are collected by conducting a wide survey and is prepared and modeled suitably. Then the a priori algorithm is implemented for discovering the frequent itemsets and the association rules. The discovered rules are then classified based on the kind of jobs and also based on the kinds of qualifications. The discovered results are analyzed and interpreted and the computational performances are also analyzed.

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Vol. 9 No. 2 (2018): March-April 2018
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Author Biography

Pankaj Kumar Deva Sarma, Department of Computer Science, Assam University, SILCHAR, ASSAM PIN 788 011

Pankaj Kumar Deva Sarma is a Ph. D. in Computer Science from Gauhati University, India in Data Mining and Knowledge Discovery. He received the B.Sc (Honours) and M. Sc. Degrees in Physics from the University of Delhi, Delhi, India before receiving the Post Graduate Diploma in Computer Application and the M. Tech degree in Computer Science from New Delhi, India. He is currently an associate professor of Computer Science in the University Department of Computer Science at the Assam University, Silchar, India. His primary research interest is in algorithms, data base systems, data mining and knowledge discovery, parallel and distributed computing, artificial intelligence and neural network. He is life member of ISTE and IETE, New Delhi.

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