An Efficient Keyword Based Searching Techniques For Optimised Retrieving And Mining Frequent Datasets

Abstract

Data Mining extracts knowledge from large databases to discover existing and newer patterns. Data mining is the technique of automatic finding of hidden valuable patterns and relationships from huge volume of data stored in databases in order to help make better business decisions. Discovering useful patterns hidden in a database plays an essential role in several data mining tasks. Frequent patterns are patterns (such as itemsets, subsequences, or substructures) that appear in a data set frequently. A substructure can refer to different structural forms, such as subgraphs, subtrees, or sublattices, which may be combined with itemsets or subsequences. If a substructure occurs frequently, it is called a (frequent) structured pattern. Finding such frequent patterns plays an essential role in mining associations, correlations, and many other interesting relationships among data. Moreover, it helps in data classification, clustering, and other data mining tasks as well. Thus, frequent pattern mining has become an important data mining task and a focused theme in data mining research. Frequent itemsets find application in a number of real- life contexts. The proposed system retrieves the optimized dataset in an efficient manner thereby mining the efficient data from the wide range of datasets.