Volume 19, No. 2, 2022

A Novel Matx-V Algorithm For College Course Demand And Admission Rate Prediction Using Sequential Pattern Mining


Mrs. VANI .N , Dr. VEERAGANGADHAR SWAMY .T.M

Abstract

The Sequential pattern mining does quintessence of patterns from quest of information dumped from large number of social media companies such as Google, Yahoo, Amazon, Flipcart and soon. Sequential pattern algorithms are very amelioration in extrication of knowledgeable patterns in various applications such as DNA analysis, Stock market, Intrusion detection etc. the extant algorithms are GSP, Prefix Span, SPADE, FAST and Lapin having numerous of pitfalls such as enormous of Time depletion, memory exhaustion and Complexity in investigating large amount of candidate sequence for macro databases. In this paper, a novel SPM technique for college course demand prediction and admission rate prediction is proposed using the MATX-V model. In the proposed work, the college log dataset is taken as input to predict the course demand and admission rates in college. Initially, preprocessing of the dataset is carried out. After that, user identification is performed to predict user behavior for future requests and then session identification takes place. Next, the proposed Mathematical model for Matrix Manipulation (MATX-V) is used to identify the frequent patterns in the dataset. Here, four different types of sequential database scanning are done by computing the centroid points and parsing them on the dataset. The proposed MATX-V algorithm uses Rabin-Karp Algorithm (RKA) for frequent pattern searching. At last, the frequent patterns obtained during scanning are stored by means of queuing technique. The outcomes of the MATX_V model demonstrate better results in terms of time and space efficiency and also the course demand and admission rates of college are predicted efficiently compared to the state-of-art methods.


Pages: 3676-3693

Keywords: Sequential pattern mining (SPM), Rabin-Karp Algorithm (RKA), Demand prediction, Sequential analysis, Admission rate prediction, Preprocessing, Mathematical model for Matrix Manipulation (MATX-V).

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