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A Comparison of ABK-Means Algorithm with Traditional Algorithms

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A Comparison of ABK-Means Algorithm with Traditional Algorithms


Ms. H. N. Gangavane

https://doi.org/10.31142/ijtsrd2197



Ms. H. N. Gangavane "A Comparison of ABK-Means Algorithm with Traditional Algorithms" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-4, June 2017, pp.614-621, URL: https://www.ijtsrd.com/papers/ijtsrd2197.pdf

Crime investigation has very difficult task for police.Department of police plays an important role for identifying the criminals and their related information. It is observable that there are so manyamounts of increases in the crime rate due to the gap between the limitedusagesof investigation technologies. So, there are various new opportunities for the developing a new methodologies and techniques in this field for crime investigation. Using the methods like image processing, based on data mining, forensic, and social mining. Developing a good crime analysis tool to identify crime patterns quickly and efficiently for future crime pattern detection is required. Data mining is a process that uses a variety of data analysis tools to discover patterns and relationships in data that may be used to make valid predictions. Data mining techniques are the result of a long process of research and product development. Data mining is the computer-assisted process to break up through and analyzing large amount of data. Then extracting the meaningfuldata. The proposed terminology provides combine approach of preprocessing by NLP clustering, outlier detection and rule engine to identify the criminals. To automatically group the retrieved data into a list of meaningful categories different clustering techniques can be used here we used the new approach to clustering i.e combination of K-medoid and Bisecting K-means algorithm for clustering. Crime area somewhat helps to find out the criminals so in this work we focus on area wise analysis with require records. Those records having all information about criminals which helps to further investigation. In this paper we compare ABK-means algorithm with three basic clustering algorithms i.e. K-means K-medoid, and Bisecting K-means on crime Denver dataset on the basis of time and accuracy.

Crime Dataset, NLP, Adaptive-Bisecting K-Means, Clustering,Rule Engine, Area-base and Cluster base graph


IJTSRD2197
Volume-1 | Issue-4, June 2017
614-621
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

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