Placement Prediction Analysis in University Using Improved Decision Tree Based Algorithm

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2014 by IJCTT Journal
Volume-17 Number-4
Year of Publication : 2014
Authors : Dammalapati Rama Krishna, Bode Prasad, Teki Satyanarayana Murthy
DOI :  10.14445/22312803/IJCTT-V17P136

MLA

Dammalapati Rama Krishna, Bode Prasad, Teki Satyanarayana Murthy "Placement Prediction Analysis in University Using Improved Decision Tree Based Algorithm". International Journal of Computer Trends and Technology (IJCTT) V17(4):190-195, Nov 2014. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
Data mining is an emerging research area applied where researchers applies for science and business application. In this paper data mining techniques are apply to placement prediction where recruitment taken place. Recruitment is one of the most important functions for any organization as they seek talented and qualified professionals to fill up their positions. Majority of the companies have been focusing on campus recruitment to fill up their positions. This method is the best way to get the right resources at the right time in the corporate world the young budding engineers. The focus of this paper is to identify whether the student will get placement or not. While the industry get the best talent from different institutes/universities, students too get chance to start their career with some of the best but it is very difficult in getting the placements. The result of this paper will assist will improve the performance of students in terms of placement. By applying the Improved Decision Tree Based classification algorithms on this data, we have predicted that students will placed in Recruitment Drives.

References
[1] Han, J. and Kamber, M., (2006) Data Mining: Concepts and Techniques, Elsevier.
[2] Dunham, M.H., (2003) Data Mining: Introductory and Advanced Topics, Pearson Education Inc.
[3] Kantardzic, M., (2011) Data Mining: Concepts, Models, Methods and Algorithms, Wiley-IEEE Press.
[4] Ming, H., Wenying, N. and Xu, L., (2009) “An improved decision tree classification algorithm based on ID3 and the application in score analysis”, Chinese Control and Decision Conference (CCDC), pp1876-1879.
[5] Xiaoliang, Z., Jian, W., Hongcan Y., and Shangzhuo, W., (2009) “Research and Application of the improved Algorithm C4.5 on Decision Tree”, International Conference on Test and Measurement (ICTM), Vol. 2, pp184-187.
[6] CodeIgnitor User Guide Version 2.14, http://ellislab.com/codeigniter/user-guide/toc.html
[7] RapidMiner, http://rapid-i.com/content/view/181/190/
[8] MySQL – The world’s most popular open source database, http://www.mysql.com/
[9] PuiK.Fong and Jens H. Weber-Jahnke,SeniorMember,IEEE Computer Society,”Privacy Preserving Decision Tree Learning Using Unrealized Data Sets”.
[10] S. Ajmani,R.morris, and B. Liskov,”A trusted third –party computation service,” Technical Report MIT-LCS-TR-847.MIT,2001
[11] .LWangandA.Jafari,”HidingSenstitivePredictiveAssociationRules ,” proc. IEEE int’l Conf.Systems,M an and Cybernetics,pp. 164-169,2005
[12] R.Agrawal and R.Srikant,”privacy preserving datamining,”proc.ACMSIGMODconf.management of data (SIGMOD ’00),pp.439-450, may 2000.
[13] ] Q.Ma and P Deng,”Secure Multi-Party protocols for Privacy Preserving Data mining ,”proc.ThirdInt’lConf.WirelessAlgorithm,Systems, and A pplications(WASA ‘08),pp.526-537,2008.
[14] J.Githanjali,J.Indumathi,N.C.Iyengar, and N.Sriman,”A Pristine clean Cabalistic ForutityStrategizeBased Approach for Incremental Data Stream Privacy Preserving Data Mining,”proc. IEEE Second Int’l Advance Computing Conf.(IACC),pp.410-415,2010
[15] N.Lomas,”Data on 84,000 United Kingdom Prisoners is Lost,” Retrieved sept.12, 2008, http://news.cnet.com/8301-1009_3-10024550-83.html, aug. 2008.
[16] ] BBC News Brown Apologises for Records Loss. Retrieved sept.12, 2008, http://news.bbc.co.uk/2/hi/uk_news/politics/7104945.stm,nov. 2007
[17] D.Kaplan,Hackers Steal 22,000 social Security Numbers From Univ. Of Missouri Database, Retrivedsept.2008, http://www.scmagazineus.com/Hackers-steal-22000-Social- Security -numbers-from-univ -of-Missouri-database/article/34964/,May 2007.
[18] D.Goodin,”Hackers Infiltrate TD Ameritrade CLIENT Database,”Retrived Sept2008, http://www.channelregister.co.uk/2007/09/15/ameritrade_database_burgled/, sept.2007.
[19] L.Liu, M kantarcioglu, and B. Thuraisingham, “Privacy Preserving Decision Tree Mining from Perturbed data ,” proc. 42nd Hawaii Int’l conf System Sciences (HICSS ’09),2009
[20] Y.Zhu,LHuang,WYang,DLi,Y.Luo,andF.Dong, “Three new approaches to privacy-preserving Add to multiply protocol and its application”,Proc.second int’l workshop knowledge discovery and dataming,(WKDD’09),pp.554 558,2009
[21] C.Aggarwal and P.Yu, Privacy preserving data mining:,models and algorithms.Springer,2008.
[22] L. Shaneck and Y.Kim “Efficient cryptographic primitives for private datamining”,Proc.43rd Hawaii int’l conf.systemsciences(HICSS),pp.1-9,2010.
[23] Varidyaand C. Clifton , “privacy preserving association rule mining in vertically partitioned data “, proc .Eighth ACM SIGKDD int’l Conf. Knowledge discovery and data mining(KDD ’02),PP.23-26,July 2002

Keywords
Classification, Decision Tree, Data Mining, Educational Research, Placement, Predicting Performance, Decision tree