Abstract
In the last few decades data mining is one of the important research areas in data maintenance of computing. In computing world, plentiful algorithms are proposed for mining. The few applications of data mining are web mining, video mining, knowledge mining and string mining. In these applications, string mining is focused and concentrated to overcome the space allocation process. To overcome the drawback suffered by the space allocation process Efficient String Mining (ESM) algorithm is proposed. The ESM algorithm performs operation faster, helps in reducing the space allocation, which in turn improves the performance of string mining and it is also possible to locate patterns that recurrent in the string database or file with a given support.
Highlights
Knowledge Engineering is a production restraint which involves desegregating knowledge into computer system so as to unravel advanced issues which normally requires a high level of creature capability
The mechanized, prospective analyses offered by data mining move beyond the analyses of past measures provided by demonstration tools typical of decision support systems
Jasbir et al (2012a) have proposed rising substring patterns from databases of string that have been exposed, which pass through an enhanced suffix array data structure
Summary
Knowledge Engineering is a production restraint which involves desegregating knowledge into computer system so as to unravel advanced issues which normally requires a high level of creature capability. At present, it refers to the building, maintaining and extension of knowledge-based systems. It refers to the building, maintaining and extension of knowledge-based systems It has an immense convention in common with software engineering and is employed in several computing engineering domains such as artificial intelligence, including databases, data mining, skilled systems, decision support systems and geographic data systems. Spectacularly less memory is utilized than the other algorithms
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