A NOVEL APPROACH FOR RECRUITMENT PROCESS IN HUMAN RESOURCES MANAGEMENT

Discovering and using valuable and meaningful data which is hidden in large databases can have strategic importance in the managerial decision making process for organizations to gain competitive advantage. With the increasing data flow, it has become more difficult for organizations to store this data and gain useful knowledge to manage their business operations and functions. Knowledge discovery process that is based on data mining methods has widely been used in business operations and management functions.This paper investigates formal concept analysis which is a powerful tool in knowledge representation and discovery and explains association rule mining based-on formal concept analysis. An experimental study is given for employee selection function ofHRM by using formal concept analysis method to model the qualifications of candidates which are needed for the job position. The qualifications of the candidates are modelled with concept lattices and the qualifications of the candidates are matched with the ones determined in the job specification.

An Incremental Algorithm for Concept Lattice Based on SSIM

As an effective tool for data analysis, Formal Concept Analysis (FCA) is widely used in software engineering and machine learning. The construction of concept lattice is a key step of the FCA. How to effectively update the concept lattice is still an open, interesting and important issue. The main aim of this paper is to provide a solution to this problem. So, we propose an incremental algorithm for concept lattice based on image structure similarity (SsimAddExtent). In addition, we perform time complexity analysis and experiments to show effectiveness of algorithm.

Formal concept analysis model for static code analysis

Tools that focus on static code analysis for early error detection are of utmost importance in software development, especially since the propagation of errors is strongly related to higher costs in the development process. Formal Concept Analysis is a prominent field of applied mathematics that uses conceptual landscapes to discover and represent maximal clusters of data. Its expressive visualization method makes it suitable for exploratory analyses in different fields. In this paper we present a Formal Concept Analysis framework for static code analysis that can serve as a model for quantitative and qualitative exploration and interpretation of such results.