University CS 450 Data Mining‚ Fall 2014 Take-Home Test N#1 Date: September 22nd‚ 2014 Final deadline for submission September 29th‚ 2014 Weighting: 5% Total number of points: 100 Instructions: 1. Attempt all questions. 2. This is an individual test. No collaboration is permitted for assessment items. All submitted materials must be a result of your own work. Part I Question 1 [20 points] Discuss whether or not each of the following activities is a data mining task.
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Inventory-Related Fraud Detection: • Beside revenue related fraud‚ the Antars also overstated their inventory. If inventory is overstated‚ the cost of goods sold is understated‚ and gross margins and net incomes are overstated. o Crazy Eddie had a close relationship with one of their vendors known as Wren Distributors. Crazy Eddie was Wren’s largest customer‚ accounting for 35% of their revenues. o Crazy Eddie ordered 10% of their total inventory from Wren so Sam Antar asked Wren to ship $3
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Chapter 1 | | Association of Certified Fraud Examiners (ACFE) | An international organization of approximately 50‚000 members based in Austin‚ Texas‚ dedicated to fighting fraud and white-collar crime. | Civil law | The body of law that provides remedies for violation of private rights—deals with rights and duties between individuals. | Criminal law | The branch of law that deals with offenses of a public nature or against society. | Customer fraud | Customers not paying for goods purchased
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Ensuring Data Storage Security in Cloud Computing Cong Wang‚ Qian Wang‚ and Kui Ren Department of ECE Illinois Institute of Technology Email: {cwang‚ qwang‚ kren}@ece.iit.edu Wenjing Lou Department of ECE Worcester Polytechnic Institute Email: wjlou@ece.wpi.edu Abstract—Cloud Computing has been envisioned as the nextgeneration architecture of IT Enterprise. In contrast to traditional solutions‚ where the IT services are under proper physical‚ logical and personnel controls‚ Cloud Computing
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university CASE STUDY OF DATA MINING Summitted by Jatin Sharma Roll no -32. Reg. no 10802192 A case study in Data Warehousing and Data mining Using the SAS System. Data Warehouses The drop in price of data storage has given companies willing to make the investment a tremendous resource: Data about their customers
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IT433 Data Warehousing and Data Mining — Data Preprocessing — 1 Data Preprocessing • Why preprocess the data? • Descriptive data summarization • Data cleaning • Data integration and transformation • Data reduction • Discretization and concept hierarchy generation • Summary 2 Why Data Preprocessing? • Data in the real world is dirty – incomplete: lacking attribute values‚ lacking certain attributes of interest‚ or containing only aggregate data • e.g.‚ occupation=“ ”
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The Bible & Accounting Fraud Liberty University Abstract Accounting is an information and measurement system used by mainly all businesses and organizations to provide relevant‚ reliable and comparable information about its business activities‚ (Wild‚ & Shaw‚ & Chiappetta‚ 2011‚ p.272). Accounting Information Systems is a fundamental part of determining the success of an organization. An effective information system provides Internal
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Data Mining Information Systems for Decision Making 10 December 2013 Abstract Data mining the next big thing in technology‚ if used properly it can give businesses the advance knowledge of when they are going to lose customers or make them happy. There are many benefits of data mining and it can be accomplished in different ways. The problem with data mining is that it is only as reliable as the data going in and the way it is handled. There are also privacy concerns with data mining
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survey especially through the Internet and questionnaires. The description of source of data and sample The researcher have a survey will be used in this proposed study where in 25 2nd year BSIT Students From Interface Computer College in Davao City‚ Because they have their own knowledge about the effects of Social Networking Sites on their academic performance. Procedure on Data Gathering We gather our data first‚ by conducting a survey. Second‚ we research on the internet. The Instruments The
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business intelligence‚ data warehouse‚ data mining‚ text and web mining‚ and knowledge management. Justify and synthesis your answers/viewpoints with examples (e.g. eBay case) and findings from literature/articles. To understand the relationships between these terms‚ definition of each term should be illustrated. Firstly‚ business intelligence (BI) in most resource has been defined as a broad term that combines many tools and technologies‚ used to extract useful meaning of enterprise data in order to help
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