Novel Approach to Seat Matrix Prediction using Hadoop - Ravikiran, MD; Gouli, Poonam (International Journal of Computer Sciences and Engineering, 2025)
Big data is a term that is used to describe huge data sets having large, varied and complex structure with the hardness of analysing, storing and visualizing for further analysis or results. The analysis into large amounts of data to expose secret correlations and hidden patterns can be termed as big data analytics. [1] Big Data has proved to be beneficial as it helps to gain richer and deeper insights into the underlying mass of data. Common Entrance Test is a flat form for the students to opt for colleges to pursue Under graduation. Every year approximately 150000 students take up CET. Thus, these students will compete for seat among 220 engineering colleges across Karnataka, that are enrolled to the CET cell. Student can opt for a College based on availability of seat or branch for the rank they obtain in CET. Predictive analytics is the basic enabler for big data. On a day to day basis, Businesses collect large quantity of customer data which is used by predictive analytics along with historical data, coupled with customer insight, to forecast future events. For predicting a college several tools are taken into consideration they are: HBase for database, MapReduce for data processing mahout’s distributed naive Bayes classification for classifying and training data.