Similarities and Dissimilarities and Data Mining Applications DEEPAK KUMAR D R M.SC IN COMPUTER SCIENCE 3RD SEMESTER‚ DAVANGERE UNIVERSITY deepakrdevang@gmail.com Abstract: This topic is mainly used by a number of data mining techniques‚ such as clustering‚ nearest neighbor classification‚ and anomaly detection. And it can also include the data mining applications.In this paper we have focused a variety of techniques‚ approaches and different areas of the research which are helpful and marked as the
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Establishing a Center of Excellence for Data Mining in Egypt By: Aref Rashad I- Introduction The convergence of computer resources connected via a global network has created an information tool of unprecedented power‚ a tool in its infancy. The global network is awash with data‚ uncoordinated‚ unexplored‚ but potentially containing information and knowledge of immense economic and technical significance. It is the role of data mining technologies arising from many discipline areas to convert
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Chapter-1: Exercise Solution 1.1 In a multiprogramming and time-sharing environment‚ several users share the system simultaneously. This situation can result in various security problems. a. What are two such problems? b. Can we ensure the same degree of security in a time-shared machine as in a dedicated machine? Explain your answer. Answer: a. Stealing or copying one’s programs or data; using system resources (CPU‚ memory‚ disk space‚ peripherals) without proper accounting. b. Probably not‚ since
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International Journal of Computer Trends and Technology (IJCTT) – volume 7 number 1– Jan 2014 Early Proliferation Stage of Detecting Diabetic Retinopathy Using Bayesian Classifier Based Level Set Segmentation S.Vijayalakshmi1‚ P.Sivaprakasam2 1 (Research Scholar‚ Karpagam University‚Coimbatore‚ India) (Department of MCA‚ Park College of Engineering and Technology‚ Coimbatore‚ India) 2 (Department of Computer Science‚ Associate Professor Sri Vasavi College‚ Erode‚ India) 1 ABSTRACT
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Data mining is a concept that companies use to gain new customers or clients in an effort to make their business and profits grow. The ability to use data mining can result in the accrual of new customers by taking the new information and advertising to customers who are either not currently utilizing the business ’s product or also in winning additional customers that may be purchasing from the competitor. Generally‚ data are any “facts‚ numbers‚ or text that can be processed by a computer.” Today
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Web Mining Data mining is the nontrivial process of identifying valid novel‚ potentially useful‚ and ultimately understandable patterns in data – Fayyad. The most commonly used techniques in data mining is artificial neural networks‚ decision trees‚ genetic algorithm‚ nearest_neighbour method‚ and rule induction. Data mining research has drawn on a number of other fields such as inductive learning‚ machine learning and statistics etc. Machine learning – is the automation of a learning process
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An examination of the global strategies of Coca-Cola Mo El Ramahi Coca- Cola is one of the most recognized brands in the world. Multi-national corporations use a variety of strategies to market products‚ such as Levitt’s globalization approach‚ known as “think global‚ act global.” Rather Coca- Cola has adopted a “think global‚ act local” strategy (local in this context refers to national‚ sub-national and world-regional markets). The objective of this paper is to provide validity for the usage of
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population is distributed by identifying two basic properties. 1. Concentration 2. Density Population concentrations -two thirds of the world’s population is clustered in 4 regions: East Asia‚ South Asia‚ Southeast Asia‚ and Western Europe. - The clustering of the world’s population can be displayed on a cartogram‚ which despites a countries size according to its population not its land area. Major population clusters -1/5 of the world’s population lives in east Asia. -1/5 of population lives in
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introduced as an incentive fee where it act as bonus for investment bank when they performance better than expected. There has been evidence of clustering of spreads internationally‚ in the US spread is clustered at 7%( Chen+Ritter 2000)‚ in Hong Kong 95% of fees are clustered at 2.5%( torstia 2003) and in Europe fees range from 3-4%. In general‚ the more clustering presented in a country‚ the smaller the spread‚ vice versa. Furthermore‚ Esho et al (2004) analyzed the underwriting spread in Euro market
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industry 5 CRM Strategy of Courier Industry 7 Customer value approach of Courier Industry 8 Tools‚ Techniques and Application of Data mining 9 Current Process of Data mining Implemented by Courier Service Organizations 12 Data Mining using Clustering Technique 14 Further Analysis with Tree Map & Industry Attributes 18 Data Mining Application on CRM and its Impact on the Industry 21 Case Studies 23 Conclusion: 25 References: 26 Executive Summary The importance of data mining and its
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