Rank Prediction for Articles and Conference Papers using Machine Learning Techniques
P.Subhashini1, K. SatyaVijaya2, G.S.K.Bhargav3, V.Vjiay Kumar4
1P. Subhashini, Department of CSE, Koneru Lakshmaiah Education Foundation, Andhra Pradesh, India.
2K. SatyaVijaya, Department of CSE, Koneru Lakshmaiah Education Foundation, Andhra Pradesh, India.
3G.S.K Bhargav, Department of CSE, Koneru Lakshmaiah Education Foundation, Andhra Pradesh, India.
4V. Vijay Kumar, Department of CSE, professor at Koneru Lakshmaiah Education Foundation, Andhra Pradesh, India.
Manuscript received on November 19, 2019. | Revised Manuscript received on November 29 2019. | Manuscript published on 30 November, 2019. | PP: 9746-9750 | Volume-8 Issue-4, November 2019. | Retrieval Number: D9257118419/2019©BEIESP | DOI: 10.35940/ijrte.D9257.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Searching for an optimal article which was given highest and best priority is quite harder based on requirements. Ranking is one of the best measure or a method to get the best rated and optimal article or a conference or a research paper through this huge Internet World. As Technology been increasing day by day Artificial Intelligence is the first step to get through any problem for a solution Machine learning is also an important aspect of Artificial Intelligence. Machine Learning is best known for classifying, categorizing and predicting. Rank prediction can be done through many different algorithm implementations in machine learning. But choosing the best is important for accurate results. This paper gives the most accurate results of algorithms that can be used for rank predictions for articles. To simplify and resolve this problem, solutions were given in many different ways but to achieve accuracy is necessary, in previous models this is given using supervised learning only. We proposed this research work with perfect results using both supervised and unsupervised learning. Neural Networks is the best algorithm in supervised learning for classifying and predicting within data. In unsupervised learning we used K-means clustering because of grouping the data. This work helps the user(s) for optimal search of an article and also gives a competitive spirit for author to get into the top, totally this is implemented using Machine Learning Techniques of Neural Networks, K-Means Algorithm which is a mixture of supervised and unsupervised learning for predicting ranks.
Keywords: Rank Predictions, Neural Networks, K-Means, Top Ranked Articles, Accuracy.
Scope of the Article: Machine Learning.