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Materialized View Generation Using Apriori Algorithm
Author(s) -
Debabrata Datta,
Kashi Nath Dey
Publication year - 2015
Publication title -
international journal of database management systems
Language(s) - English
Resource type - Journals
eISSN - 0975-5985
pISSN - 0975-5705
DOI - 10.5121/ijdms.2015.7602
Subject(s) - computer science , apriori algorithm , a priori and a posteriori , data mining , algorithm , association rule learning , philosophy , epistemology
Data analysis is an important issue in business world in many respects. Different business organizations\udhave data scientists, knowledge workers to analyze the business patterns and the customer behavior.\udScrutinizing the past data to predict the future result has many aspects and understanding the nature of the\udquery is one of them. Business analysts try to do this from a big data set which may be stored in the form of\uddata warehouse. In this context, analysis of historical data has become a subject of interest. Regarding this,\uddifferent techniques are being developed to study the pattern of customer behavior. Materialized view is a\uddatabase object which can be extensively used in data analysis. Different approaches are there to generate\udoptimum materialized view. This paper proposes an algorithm which generates a materialized view by\udconsidering the frequencies of the attributes taken from a database with the help of Apriori algorithm

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