Sunita B. Aher

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Data mining, the extraction of hidden predictive information from large databases, is a powerful new technology with great potential used in various commercial applications including retail sales, e-commerce, remote sensing, bioinformatics etc. Education is an essential element for the progress of country. Mining in educational environment is called(More)
The ADTree (Alternating Decision Tree) is a supervised classification technique that combines decision trees with the predictive accuracy into a set of classification rules & association rule algorithms are used to show the relationship between data items. Here in this paper we combine these two algorithms & apply it to sample data obtained from Moodle(More)
Data Mining is the extraction of hidden predictive information from large database which can be used in various commercial applications like bioinformatics, E-commerce etc. Association Rule, classification and clustering are three different algorithms in data mining. Course Recommender System plays an important role in identifying the behavior of students(More)
Data mining also known as Knowledge Discovery in Database is the process of discovering new pattern from large data set. E-learning is the electronically learning & teaching process. Course Recommender System allows us to study the behavior of student regarding the courses. In Course Recommender System in E-learning, we collect the data regarding the(More)
In this paper we consider the applicability of data mining algorithms such as clustering & association rule algorithm for recommending the courses to the student in E-Learning System e.g. the student who liked to study the course "Operating System" is quite like to study the course "Distributed System". We develop the algorithm in java which is the(More)
Content-Centric Networks (CCNs) have recently emerged as an innovative trend to overcome many inherent security problems in the IP-based (host-based) networks by securing the content itself rather than the channel through which it travels. In this network architecture new kinds of attacks-ranging from DoS to privacy attacks-will appear. Therefore, it is(More)
Data preparation is the important step in Course Recommendation System which aims at predicting the course selected by student. In this paper we present the data preparation strategy for Course Recommendation System. Here we have used the real data of courses offered through Moodle package of the college & apply the data preparation strategy to it to find(More)
University servers and databases store a huge amount of data including personal details, registration details, evaluation assessment, performance profiles, and many more for students and lecturers alike. Mining such data offers a huge potential in advancing the educational field in the country because data mining is able to extract important models and(More)
Course recommender system aims at predicting the best combination of courses selected by students. Here in this paper we present how the combination of clustering algorithm-Simple K-means Algorithm & association rule algorithm-Apriori Association Rule is useful in Course Recommender system. If we use only the Apriori association rule algorithm then we need(More)