Managing Knowledge in organizations G.O. KAYODE-ADEDEJI SCHOOL OF ENGINEERING‚ DESIGN and TECHNOLOGY UNIVERSITY OF BRADFORD G.O.Kayode-Adedeji@bradford.ac.uk 2011 [Type the company name] 1/1/2011 Contents Introduction 2 KNOWLEDGE MANAGEMENT VS INFORMATION MANAGEMENT 5 KNOWLEDGE MANAGEMENT CONTROVERSIES 5 POSSIBLE CONSTRAINTS IN THE IMPLEMENTATION OF A KNOWLEDGE MANAGEMENT PROGRAM 6 CASE STUDY ON THE SUCCESSFUL IMPLEMENTATION OF KM: 6 THE EVOLUTION OF KM AT BUCKMAN LABORATORIES
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Data Mining: Introduction Lecture Notes for Chapter 1 Introduction to Data Mining by Tan‚ Steinbach‚ Kumar © Tan‚Steinbach‚ Kumar Introduction to Data Mining 4/18/2004 1 Why Mine Data? Commercial Viewpoint O Lots of data is being collected and warehoused – Web data‚ e-commerce – purchases at department/ grocery stores – Bank/Credit Card transactions O Computers have become cheaper and more powerful O Competitive Pressure is Strong – Provide better‚ customized services for an edge (e.g
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Recommended Systems using Collaborative Filtering and Classification Algorithms in Data Mining Dhwani Shah 2008A7PS097G Mentor – Mrs. Shubhangi Gawali BITSC331 2011 1 BITS – Pilani‚ K.K Birla Goa INDEX S. No. 1. 2. 3. 4. 5. 6. 7. 8. 9. Topic Introduction to Recommended Systems Problem Statement Apriori Algorithm Pseudo Code Apriori algorithm Example Classification Classification Techniques k-NN algorithm Determine a good value of k References Page No. 3 5 5 7 14 16 19 24 26 2
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manage large volumes of business data. The use of database systems in supporting applications that employ query based report generation continues to be the main traditional use of this technology. However‚ the size and volume of data being managed raises new and interesting issues. Can we utilize methods wherein the data can help businesses achieve competitive advantage‚ can the data be used to model underlying business processes‚ and can we gain insights from the data to help improve business processes
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with Data Mining Abstract Banking and finance institutions are growing very fast in this globalization era. Mergers‚ acquisitions‚ globalization have made these institutions bigger. No doubt‚ the data also grow real huge and more varied. Big data storage such as data warehouse and data marts are provided to give a solution on big data storage. On the other sides‚ those data are needed to be analyzed. Business intelligence finally comes in as a solution in analyzing those huge data. Business
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International Journal of Computer Applications (0975 – 8887) Volume 41– No.5‚ March 2012 Data Mining Application in Enrollment Management: A Case Study Surjeet Kumar Yadav Saurabh pal Research scholar‚ Shri Venkateshwara University‚ J. P. Nagar‚ (U.P.) India Head‚ Dept. of MCA VBS Purvanchal University‚ Jaunpur‚ India ABSTRACT In the last two decades‚ number of Higher Education Institutions (HEI) grows rapidly in India. This causes a cut throat competition among these institutions
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and KNN algorithms‚ I will create a training model and try apply the class survived or didn’t survive. If I apply a decision tree to the dataset as it is‚ I get a prediction rate of 78%. I will try various techniques throughout this report to increase the overall prediction rate. Data mining objectives: I would like to explore the pre conceived ideas I have about the sinking of the titanic‚ and prove if they are correct. Was there a majority of 3rd class passengers who died? What was the ratio
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Learning and Data Mining Overview: Efficient asset allocation through statistical learning methods and comparison of methods for the creation of an index tracking ETF (Exchange traded fund) Datasets: The datasets are chosen from the website of the book “Statistics and Data Analysis for Financial Engineering” by David Ruppert. The book is mentioned as one of the references for this course. The two data sets chosen are 1. Stock_FX_Bond.csv 2. Stock_FX_Bond_2004_to_2006.csv The data includes
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CHAPTER 1 An introduction to Internet marketing The Internet and the marketing concept..................................................................................... 4 Internet marketing defined ......................................................................................................... 8 What benefits does the Internet provide for the marketer? ...................................................... 20 A short introduction to Internet technology .......................
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Data Mining and Actionable Information May 24‚ 2014 Data Mining and Actionable Information People need information for planning their work‚ meet deadlines‚ and achieve their goals. They also need information to analyze problems and make important decisions. Data is most definitely not in short supply these days‚ but not all data is useful or reliable. Actionable information offers data that can be used to make effective and specific business decisions (Soatto‚ 2009). In order
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