Data Mining and Knowledge Engineering

R. Sridhar ¹, S. Balasubramanian ²

Affiliations
1 Department of MCA, SRMVCAS, Coimbatore, IN
2 JSS University, Mysore, IN

Abstract

Human development depends on Physical health, Aptitude and Attitude. Physical health refers to Overweight, Normal and Underweight using Body Mass Index. Aptitude refers to intellectual ability or talent to solve the problem and Attitude refers to gunas which indicates the 'inherent energy or tendency' with which the mind functions. Attitude are categorized as Sattvic, Rajasic and Tamasic type. Aptitude are classified as high, medium and low. We developed statistical based method and Fuzzy Logic based method, to find the relationship between attitude, aptitude and physical. 535 males and 320 females were given questionnaire based on attitude, aptitude and physical. We are able to find each individual inherent tendency with intellectual ability and physical has no effect on it. Males are rajasic nature with low aptitude and females are rajasic nature with medium aptitude. The inherent tendency of 855 candidates are rajasic nature with low aptitude. Attitude plays dominant role in the development of aptitude.

Keywords

Attitude, Aptitude, Fuzzy Logic, BMI.

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A. Thangavelu ¹, S. R. Sathyaraj ¹, R. Sridhar ², S. Balasubramanian ³

Affiliations
1 DRDO-BU CLS, Bharathiar University, Coimbatore-641046, IN
2 Sri Ramakrishna Mission Vidyalaya, Coimbatore-641020, IN
3 CJSS University, Mysore-500015, IN

Abstract

In this paper which passion to integrate a large volume of data sets into useful information by adopting a various information techniques in the most modern technology world. The adopted approaches of Single variate Association Rule for Area to Crime based on the knowledge discovery techniques such as, clustering and association-rule mining. It reveals with an inherent of patterns of information into a fruitful exploratory tool for the discovery of spatio-temporal patterns. This tool is an autonomous pattern detector to reveal plausible cause-effect associations between layers of point and area data. We present VATA algorithm with an exploratory analysis for the effectively explore geo-referenced data. The present study of this paper was focuses through the real crime dataset by using algorithm. We demonstrate approach to a new type of analysis of the spatio-temporal dimensions of records of criminal events. We hope this will lead to new approaches in the exploration of large volumes of spatio-temporal data.

Keywords

Algorithm, Clustering Association Rule, Crime Data, Data Mining, GIS, Spatio-Temporal Data.

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A. Thangavelu ¹, S. R. Sathyaraj ¹, R. Sridhar ², S. Balasubramanian ³

Affiliations
1 DRDO-BU CLS, Bharathiar University, Coimbatore-641046, IN
2 Department of MCA, Sri Ramakrishna Mission Vidyalaya, Coimbatore-641020, IN
3 Department of Environmental Science, JSS University, Mysore-500015, IN

Abstract

Spatial data mining is a demanding field since huge amounts of spatial data that has been processed and turned into useful information by this paper. The increased crime rate and enormous amount of data being stored in crime databases by police personnel which has been collected from various jurisdiction of Coimbatore are gathered for the application of technologies which provides the means to turn data into information by data fusion and data mining. Data fusion organizes, combines and interprets information from multiple sources and it overcomes confusion from conflicting reports and cluttered or noisy backgrounds. Data mining is concerned with the automatic discovery of patterns and relationships with (crime to crime) in large databases. Technically, it is the process of finding correlations or patterns among dozens of fields in large relational databases using the tools of GIS. This paper provides a clear finding to prevent from crime with associated to another crime occurrence with the naked observation on correlation between one crime to another crime.

Keywords

Algorithm, Association Rule, Data Mining, Crime Data, GIS.

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