Abstract
Day by day the quantum of data has been increasing not only in terms of user generated content in social media but also outside the social media, due to which the data has gone from scarce to superabundant that conveys new advantages to users. This explosion of data has made it difficult to handle and analyze huge datasets. Therefore, the techniques of Data Mining assist in exploring and analyzing enormous datasets and helps in discovering meaningful patterns. Clustering is one such task of Data Mining that gathers all the data and partitions it into various groups taking into account their similarity or closeness measure. Clustering in the field of Social Science is used in identification, analysis and detection of various crime patterns. This paper proposes the Modified k-means clustering technique which is applied on the fictitious crime data in order to identify various crime patterns or trends and make a variety of predictions from the analysis of different crime patterns.
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Vidyavathi, B.M., Neha, D. (2018). Prediction of Crime Trends Using Mk-MC Technique. In: Satapathy, S., Bhateja, V., Raju, K., Janakiramaiah, B. (eds) Data Engineering and Intelligent Computing. Advances in Intelligent Systems and Computing, vol 542 . Springer, Singapore. https://doi.org/10.1007/978-981-10-3223-3_40
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DOI: https://doi.org/10.1007/978-981-10-3223-3_40
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