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Enhanced Multi-criteria Recommender System Based on AHP

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Applications of Soft Computing for the Web

Abstract

This chapter presents an AHP (Analytic hierarchy Process)-based method for multi-criteria decision-making problem involving college selection. The proposed method is evaluated on a sample dataset collected from U. S. news dataset. The U. S. dataset consists of ratings on various aspects of many different colleges from multiple users. We have used eight criteria and eight colleges. The method builds an analytic hierarchy structure of multiple criteria and alternatives to ease the decision-making process. The ranking of each college is based on the overall score considering multiple criteria. The experimental results demonstrate the effectiveness of the use of AHP in college selection process.

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References

  1. Walker JP (1971) Decision-making under conditions of information overload: alternative response modes and their consequences, ERIC Clearinghouse

    Google Scholar 

  2. Isinkaye FO, Folajimi YO, Ojokoh BA (2015) Recommendation systems: principles, methods and evaluation. Egypt Inform J 16(3):261–273

    Google Scholar 

  3. Jie L, Dianshuang W, Mingsong M, Wei W, Guangquan Z (2015) Recommender system application developments: a survey. Decis Support Syst  74:12–32

    Google Scholar 

  4. Adomavicius G, Tuzhilin A (2005) Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Trans Knowl Data Eng 17:734–749

    Google Scholar 

  5. Manouselis N, Drachsler H, Vuorikari R, Hummel H, Koper R (2009) Recommender systems in technology enhanced learning, Recommender Systems Handbook, pp 387–415

    Google Scholar 

  6. Saaty TL (2008) Group decision making: drawing out and reconciling differences, RWS Publications, ISBN: 188-8-603-089

    Google Scholar 

  7. Burke R (2002) Hybrid recommender systems: survey and experiments. User Model User-Adapt Interact 12(4):331–370

    Google Scholar 

  8. Adomavicius G, Kwon YO (2007) New recommendation techniques for multi-criteria rating systems. IEEE Intell Syst 22(3):1548–1555

    Google Scholar 

  9. Schafer JB, Konstan JA, Riedl J (2001) E-commerce recommendation applications. Data Min Knowl Discov 5:115–153

    Google Scholar 

  10. Bobadilla J, Ortega F, Hernando A, Gutierrez A (2013) Recommender systems survey. Knowl-Based Syst 46:109–132

    Google Scholar 

  11. Jannach D, Zanker M, Felfernig A, Friedrich G (2011) Recommender systems: an introduction, Cambridge University Press, p 336 ISBN: 978-0-521-49336-9

    Google Scholar 

  12. Fandel G, Spronk J (1983) Multiple criteria decision methods and applications. Springer, Berlin

    Google Scholar 

  13. Douligeris C, Pereira I.J (1994) A Telecommunications Quality Study Using the Analytic Hierarchy Process. IEEE J Sel Areas Commun vol 12

    Google Scholar 

  14. Tam M.C.Y, Tummala VMR (2001) An application of the AHP in vendor selection of a telecommunications system, vol 29. Omega, Elsevier, pp 171–182

    Google Scholar 

  15. Yeh C (2002) A problem-based selection of multi-attribute decision making methods. Int Trans Oper Res 9:169–181

    Google Scholar 

  16. Ariff H, Salit M.S, Ismail N, Nukman Y (2008) Use of analytical hierarchy process (AHP) for selecting the best design concept, vol 49

    Google Scholar 

  17. Simanaviciene R, Ustinovichius L (2010) Sensitivity analysis for multiple-criteria decision making methods: TOPSIS and SAW, Procedia—Social and Behavioral Sciences 2(6):7743–7744

    Google Scholar 

  18. Karami A (2011) Utilization and comparison of multi-attribute decision making techniques to rank Bayesian network options, Master Thesis, University of Skovde

    Google Scholar 

  19. Devi K, Yadav SP, Kumar S (2009) Extension of fuzzy TOPSIS method based on vague sets. Int Journal Comput Cognition 7(4)

    Google Scholar 

  20. Palanivel K, Sivakumar R (2010) Fuzzy multi-criteria decision-making approach for collaborative recommender systems. Int J Comp Theor Eng 2:1793–8201  

    Google Scholar 

  21. Frair L, Matson JE (1998) Undergraduate curriculum evaluation with the analytic hierarchy process, Frontiers in Education Conference, IEEE

    Google Scholar 

  22. Hyun G-K, Seong P-H (1999) A methodology for evaluating alarm-processing systems using informational entropy-based measure and the analytic hierarchy process. IEEE Trans Nucl Sci 46:2269–2280

    Google Scholar 

  23. Cebeci U (2009) Fuzzy AHP-based decision support system for selecting ERP systems in textile industry by using balanced scorecard. Expert Syst Appl 36(5):8900–8909

    Google Scholar 

  24. Ozcan T, Celebi N (2011) Comparative analysis of multi-criteria decision making methodologies and implementation of a warehouse location selection problem. Expert Syst Appl Int J vol 38

    Google Scholar 

  25. Yang CL, Chuang SP, Huang RH, Tai CC (2008) Location selection based on AHP/ANP approach, Industrial Engineering and Engineering Management, IEEM,  2008

    Google Scholar 

  26. Rezaiana S, Joziba SA (2012) Health-safety and environmental risk assessment of refineries using of multi-criteria decision making method. APCBEE Procedia 2:235–238

    Google Scholar 

  27. Saeed Zaeri M, Sadeghi A, Naderi A (2011) Application of multi-criteria decision making technique to evaluation suppliers in supply chain management. Afr J Math Comput Sci Res 4(3):100–106

    Google Scholar 

  28. Chang PL, Chen YC (1994) A fuzzy multi-criteria decision making method for technology transfer strategy selection in biotechnology. Fuzzy Sets Syst 63(2):131–139 

    Google Scholar 

  29. Dagdeviren M, Yavuz S, Kilinc N (2009) Weapon selecting using the AHP and TOPSIS methods under fuzzy environment. An Expert Syst Appl 36(4):8143–8151

    Google Scholar 

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Correspondence to Manish Jaiswal .

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Jaiswal, M., Dwivedi, P., Siddiqui, T.J. (2017). Enhanced Multi-criteria Recommender System Based on AHP. In: Ali, R., Beg, M. (eds) Applications of Soft Computing for the Web. Springer, Singapore. https://doi.org/10.1007/978-981-10-7098-3_3

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  • DOI: https://doi.org/10.1007/978-981-10-7098-3_3

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