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State of the Art of Prediction and Recommender System
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 108 - Number 11 |
| Year of Publication: 2014 |
| Authors: Bhakti Ratnaparkhi, J. S. Umale |
10.5120/18959-0287
|
Bhakti Ratnaparkhi, J. S. Umale . State of the Art of Prediction and Recommender System. International Journal of Computer Applications. 108, 11 ( December 2014), 38-41. DOI=10.5120/18959-0287
Abstract
Recommender system is the system which gives suggestions. It takes help of prediction system to give recommendations. Prediction system will do predictions about future actions. Recommender system provides top ranked predictions as recommendations. It is very essential to do correct prediction for giving best recommendation. In order to improve quality of recommender system researchers have been trying different approaches which we are see through this survey paper.
References
- Maria Augusta S. N. Nunes, "Towards to Psychological-based Recommenders Systems: A survey on Recommender Systems", SCIENTIA PLENA VOL. 6, NUM. 8 2010.
- Manos Papagelis, Dimitris Plexousakis, Ioannis Rousidis and Elias Theoharopoulos,"Qualitative Analysis of User-based and Item-based Prediction Algorithms for Recommendation Systems".
- Shuai Zhang, Sally I. McClean, "A Predictive Model for Assistive Technology Adoption for People With Dementia", IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, VOL. 18, NO. 1, JANUARY 2014.
- Yang Guo, Guohua Bai, Yan Hu, "Using Bayes Network for Prediction of Type-2 Diabetes", 2012, IEEE, 7th International Conference for Internet Technology and Secured Transactions (ICITST).
- Ayman Khedr,"Business Intelligence framework to support Chronic Liver Disease Treatment", International Journal of Computers & Technology Volume 4 No. 2, March-April, 2013, ISSN 2277-3061.
- Samuel and Omisore, "Hybrid Intelligent System for the Diagnosis of Typhoid Fever", J Comput Eng Inf Technol 2013, 2:2, Journal of Computer Engineering & Information Technology.
- "Diagnosis of Heart Disease for Diabetic Patients using Naive Bayes Method", International Journal of Computer Applications (0975 – 8887) Volume 24– No. 3, June 2011.
- "Finding Locally Frequent Diseases Using Modified Apriori Algorithm", International Journal of Advanced Research in Computer and Communication Engineering Vol. 2, Issue 10, October 2013.
- "Importance of Artificial Neural Network in Medical Diagnosis disease like acute nephritis disease and heart disease", International Journal of Engineering Science and Innovative Technology (IJESIT) Volume 2, Issue 2, March 2013.
- "Lung cancer differential diagnosis based on the computer assisted radiology: The state of the art"
- "The Application of Machine Learning Technique for Malaria Diagnosis"
- "Performance Evaluation of Levenberg-Marquardt Technique in Error Reduction for Diabetes Condition Classification", International Conference on Computational Science, ICCS 2013.
- "An Investigation into the Feasibility of Detecting Microscopic Disease Using Machine Learning", Keynote Lecture of IEEE International Conference on Bioinformatics and Biomedicine November 2-4, 2007, Silocon Valley, California, USA.
- Arturas Kaklauskas, Edmundas Kazimieras Zavadskas, Vaidotas Trinkunas, Laura Tupenaite, Justas Cerkauskas, Paulius Kazokaitis, "Recommender system to research students' study efficiency", Procedia - Social and Behavioral Sciences 51 ( 2012 ) 980 – 984.
- Sakchai Tangwannawit and Montean Rattanasiriwongwut, "Comparing the Strengths and Difficulties Questionnaire (SDQ) and Behavior Consideration Assessment Using SVM Techniques", DOI: 10. 7763/IPEDR. 2014. V70. 16.
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