REFERENCES ------------Journal paper-------------------- Gomes, J. Portela, F. and Santos, M. F. Data Mining Models to (2016) “Real-Time Predict Football 2-Way Result.” Jurnal Teknologi, Penerbit UTM Press. (accepted for publication) Haghighat. M. Rastegari, H. and Nourafza, N. (2013) “A Review of Data Mining in Computer Science: Techniques for Result Prediction in Sports”, ACSIJ Advances an International Journal, Vol. 2, Issue 5, No.6, pp.1-6. Joseph, A. Fenton, N.E. and Neil, M. (2006) Football Results Using “Predicting Bayesian Nets and Other Machine Learning Techniques”, Knowledge Based Systems, vol.19, no.7, pp.544-553. Pischedda, G. (2014) NHL Match Outcomes with ML Models”, “Predicting International Journal of Computer Applications, vol.101, no.9, pp.15-22. ----------Conference Proceedings--------- Buursma, D. (2011) Sports Events from Past Results”, “Predicting 14th Twente Student Conference on IT, Enschede, Netherlands Langseth, H. (2013) the Bookie: A Look at Statistical Models for “Beating at the 12th Scandinavian AI conference, Prediction of Football Matches”, Presented Aalborg, Denmark -----------Web sources----------------------- Cheng, B. Dade, K. Lipman, M. & Mills, C. (2013). the betting line in “Predicting from Stanford University, Program on Computer Science NBA games”. Retrieved Web Site: Liu, B. and Lai, P. (2010). Retrieved the NCAA Football Point Spread”. “Beating from Stanford University, Program on Computer Science Web Site:
REFERENCES ------------Journal paper-------------------- Gomes, J. Portela, F. and Santos, M. F. (2016) “Real-Time Data Mining Models to Predict Football 2-Way Result.” Jurnal Teknologi, Penerbit UTM Press. (accepted for publication) Haghighat. M. Rastegari, H. and Nourafza, N. (2013) “A Review of Data Mining Techniques for Result Prediction in Sports”, ACSIJ Advances in Computer Science: an International Journal, Vol. 2, Issue 5, No.6, pp.1-6. Joseph, A. Fenton, N.E. and Neil, M. (2006) “Predicting Football Results Using Bayesian Nets and Other Machine Learning Techniques”, Knowledge Based Systems, vol.19, no.7, pp.544-553. Pischedda, G. (2014) “Predicting NHL Match Outcomes with ML Models”, International Journal of Computer Applications, vol.101, no.9, pp.15-22. ----------Conference Proceedings--------- Buursma, D. (2011) “Predicting Sports Events from Past Results”, 14th Twente Student Conference on IT, Enschede, Netherlands Langseth, H. (2013) “Beating the Bookie: A Look at Statistical Models for Prediction of Football Matches”, Presented at the 12th Scandinavian AI conference, Aalborg, Denmark -----------Web sources----------------------- Cheng, B. Dade, K. Lipman, M. & Mills, C. (2013). “Predicting the betting line in NBA games”. Retrieved from Stanford University, Program on Computer Science Web Site: Liu, B. and Lai, P. (2010). “Beating the NCAA Football Point Spread”. Retrieved from Stanford University, Program on Computer Science Web Site:
2016%20-%20FINAL%20REPORT%20Group5.docx