online purchases. These factors have resulted in increase in the quantity of the data collected. For this reason‚ the retail industry is a major application area for data mining. This paper elaborates upon the use of the data mining technique of clustering to segment customer profiles for a retail store. Retail data mining can help identify customer buying patterns and behaviours‚ improve customer service for better customer satisfaction and hence retention. The retail industry collects huge amounts
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Expert Systems with Applications 37 (2010) 5259–5264 Contents lists available at ScienceDirect Expert Systems with Applications journal homepage: www.elsevier.com/locate/eswa Cluster analysis using data mining approach to develop CRM methodology to assess the customer loyalty Seyed Mohammad Seyed Hosseini *‚ Anahita Maleki‚ Mohammad Reza Gholamian Industrial Engineering Department‚ Iran University of Science and Technology‚ Tehran‚ Iran a r t i c l e i n f o a b s t r a c t
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Semi-Supervised K-Means Clustering for Outlier Detection in Mammogram Classification K. Thangavel1‚ A. Kaja Mohideen2 Department of Computer Science‚ Periyar University‚ Salem‚ India 1 drktvelu@yahoo.com‚ 2kaja.akm@gmail.com Abstract— Detection of outliers and relevant features are the most important process before classification. In this paper‚ a novel semi-supervised k-means clustering is proposed for outlier detection in mammogram classification. Initially the shape features are extracted
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Chapter 1 Exercises 1. What is data mining? In your answer‚ address the following: Data mining refers to the process or method that extracts or \mines" interesting knowledge or patterns from large amounts of data. (a) Is it another hype? Data mining is not another hype. Instead‚ the need for data mining has arisen due to the wide availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge. Thus‚ data mining can be viewed as the result of
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Telp. 0341-565544 Nama : Firman Agus NPM : 205.10.4.0027 Program Studi : Pendidikan Bahasa Inggris Judil Tesis : Increasing Ability to Write Draft of Composition through Clustering Technique of Eleventh Grade Students at SMK Negeri 1 Bojonegoro in Academic Year 2006/2007 ABSTRACT Key Words: Clustering‚ technique‚ draft of composition‚ increasing‚ writing skill Students often complain about writing activity in the classroom. They do not know what to write and where to
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Ramya Yapala VHDL IMPLEMENTAION USING SPIKE SORTING ALGORITHM A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE DEGREE OF MASTER OF SCIENCE IN MICRO ELECTRONICS VHDL IMPLEMENTATION USING SPIKE SORTING ALGORITHM A Thesis submitted to Newcastle University for the degree of MSc Micro Electronics 2011 Supervisor: Dr Graeme Chester Student Name: Ramya Yapala Student Number: 109230832 SCHOOL OF ELECTRICAL‚ ELECTRONIC AND COMPUTER ENGINEERING NEWCASTLE UNIVERSITY SCHOOL OF ELECTRICAL
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Non-Hierarchical Cluster Analysis Non-hierarchical cluster analysis (often known as K-means Clustering Method) forms a grouping of a set of units‚ into a pre-determined number of groups‚ using an iterative algorithm that optimizes a chosen criterion. Starting from an initial classification‚ units are transferred from one group to another or swapped with units from other groups‚ until no further improvement can be made to the criterion value. There is no guarantee that the solution thus obtained
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extends across the African continent and beyond‚ is one of the largest manufacturers and marketers of FMCG products in Southern Africa‚ and has been for several decades. Tiger Brands has been built over several decades through the acquisition and clustering of businesses which own leading food‚ home and personal care brands. It’s success is grown and maintained through the perpetual renovation and innovation of its brands‚ while its approach to expansion‚ acquisitions and joint ventures has given traction
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References: [1]GWeijie Su‚ Xin Jin‚ “Hidden Markov Model with Parameter-Optimized K-means Clustering for Handwriting Recognition”‚ International Conference on Internet Computing and Information Services‚ pp:435-438‚ 2011 [2]Karthik Sheshadri‚ Pavan Kumar T Ambekar‚ Deeksha Padma Prasad and Dr.Ramakanth P Kumar‚ “An OCR system for Printed Kannada using K-means clustering”‚ International Conference on Industrial Technology ‚pp:183-187‚ 2010 [3]Mu-King Tsay‚ Keh-Hwashyu‚ Pao-Chung
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relationships between various crimes and characteristics of crimes. Data mining methods have become the main tools to analyze data and to discover knowledge from them. Here‚ data mining refers to an integration of multiple methods such as classification‚ clustering‚ evaluation‚ and data
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