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Number 6

An Efficient Concept-based Mining Model for Deriving User Profiles

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  • International Journal of Applied Information Systems
  • Foundation of Computer Science (FCS), NY, USA
  • Volume 1 - Number 6
  • Year of Publication: 2012
  • Authors: P. Sasikala, V. Vidhya
  • 10.5120/ijais12-450187
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  • P. Sasikala and V. Vidhya 2012. An Efficient Concept-based Mining Model for Deriving User Profiles. International Journal of Applied Information Systems. 1, 6 (February 2012), 26-34. DOI=http://dx.doi.org/10.5120/ijais450187 
  • @article{10.5120/ijais2017451568,
author = {P. Sasikala and V. Vidhya },
title = {An Efficient Concept-based Mining Model for Deriving User Profiles},
journal = {International Journal of Applied Information Systems},
issue_date = {February 2012},
volume = {1},
number = {},
month = {February},
year = {2012},
issn = {},
pages = {26-34},
numpages = {},
url = {/archives/volume1/number6/99-0187},
doi = { 10.5120/ijais12-450187},
publisher = { xA9 2010 by IJAIS Journal},
address = {}
}

  • %1 450187
%A P. Sasikala
%A V. Vidhya 
%T An Efficient Concept-based Mining Model for Deriving User Profiles
%J International Journal of Applied Information Systems
%@ 
%V 1
%N 
%P 26-34
%D 2012
%I  xA9 2010 by IJAIS Journal

Abstract

Software testing is an important activity in the software development life cycle and it is widely used validation approach in software industry, deployed by programmers and testers. The program with the moderate complexity cannot be tested completely. Innovative methods are needed to perform testing as a whole and unit testing in particular with minimum effort and time. Unit testing is mostly done by developers under a lot of schedule pressure since the software companies find a compromise among functionality, time to market and quality. Thus there is a need for reducing unit testing time by optimizing and automating the process. Test suite generation is an error-prone, tedious and time consuming part of unit testing. Two techniques are proposed to automatically generate test cases from the input domain using scatter search and tabu search for branch coverage criteria with respect to cyclomatic complexity measure.

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Keywords

Clustering, Collaborative Filtering, Personalization, Query formulation, User profiles, Personality diagnosis

Index Terms

Computer Science
Information Sciences