What stocks are risky? What stocks in the portfolio that it has higher return? Many investors may use fundamental analysis to analysis financial data for answering above questions. In the last decade‚ some researches applied data mining techniques on financial market. Data mining is the process of automatically discovery useful information in large data repositories. It can be used to support a wide range of business intelligence applications such as customer profiling‚ targeted marketing‚ store
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companies had not kept their customer data in database ? This very useful for company forbes such as in learn details about each if its individual readers by examining forbes`s entire reader population. By this way they can easily understand each individual who interacts with its brand. These details help forbes advertisers target their campaigns more precisely and also help forbes publication increase their circulation. As for kodak company‚ its help to consulate the data on all of its marketing activities’
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amounts of data have been stored in computers. The existing database systems do not provide the users with the necessary tools and functionalities to capture all stored information easily. Therefore‚ automatic knowledge discovery techniques have been developed to capture and use the voluminous information hidden in large databases. Discovery of association rules is an important class of data mining‚ which is the process of extracting interesting and frequent patterns from the data. Association
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Description 2.1 Problem Definition 2.2 Problem Description 3 Data Mining Process And Implementation 3.1 Requirement analysis 3.2 Data Selection And Collection 3.3 Cleaning And Preparing Data 3.4 Data Mining Exploration And Validation 3.5 Implementing‚ Evaluating And Monitoring 3.6 Result visualization 4 Data Mining Model And Development Process 4.1 Algorithm Implementation 5 Data Mining Findings 6 Conclusion 7 Bibliography
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Above the line (ATL)‚ below the line (BTL)‚ and through the Line (TTL)‚ in organizational business and marketing communications‚ are advertising techniques. In a nutshell‚ while ATL promotions are tailored for a mass audience‚ BTL promotions are targeted at individuals according to their needs or preferences. While ATL promotions can establish brand identity‚ BTL can actually lead to a sale. ATL promotions are also difficult to measure well‚ while BTL promotions are highly measurable‚ giving marketers
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the business. Data mining techniques are not a new subject‚ but the amount of data that can be processed by the modern computers and the global market that the world has become has opened a lot of opportunities. This paper considers a method for proposal of video materials to the customers in a video on demand (VOD) system‚ but its broader usage covers any closed system in which the user is identified before the purchase and history of previous user actions is available. By usingthe data from previous
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...............................................................3 2. Related Work and Motivation 1. Coda: The Pioneering System for Hoarding................................................................4 2. Hoarding Based on Data Mining Techniques..............................................................5 3. Hoarding Techniques Based on Program Trees...........................................................8 4. Hoarding in a Distributed Environment..........
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Database: A data base is a self-describing collection of integrated records. Bytes (character of data) are grouped into columns. Columns are also called fields. Columns or fields‚ in turn‚ are grouped into rows‚ which are also called records. The collection of data for all columns is called a row or a record. A group of similar rows or records is called a table or a file. A database is a collection of tables plus relationships around the rows in those tables‚ plus special data‚ called metadata‚ that
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IS 533 HOMEWORK 4 BY AHMET CAN AYKUT (1835917) 1. What is meant by a symptom versus a problem? Relate these ideas to the case. (5 points) In the Intelligence Phase of the Decision Making Process‚ the decision maker‚ Elena‚ attempts to determine whether a problem exists‚ identify its symptoms‚ determine its magnitude and explicitly define it. What is described as a problem may only be a symptom‚ or measure‚ of a problem. In the case‚ MMS sales are off by 10 percent‚ which is the main problem
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Zanfrillo‚ Data Mining Application to Decision-Making Processes in University Management‚ INFOCOMP Journal of Computer Science‚ volume 6‚ no.1 pp.57-65‚ 2007. J. Luan‚ Data Mining Application in Higher Education‚ SPSS Executive Report‚ 2002. J. Luan‚ Data Mining as Driven by Knowledge Management in Higher Education-Persistence Clustering And Prediction‚ Keynote speech at the University of California-San Francisco ’s SPSS Public Roadshow‚ 2001. H. Jiawei and K. Micheline‚ Data Mining: Concepts and
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