Data Mining Abdullah Alshawdhabi Coleman University Simply stated data mining refers to extracting or mining knowledge from large amounts of it. The term is actually a misnomer. Remember that the mining of gold from rocks or sand is referred to as gold mining rather than rock or sand mining. Thus‚ data mining should have been more appropriately named “knowledge mining from data‚” which is unfortunately somewhat long. Knowledge mining‚ a shorter term‚ may not
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4 Components of DSS (Decision Support System) Data Store – The DSS Database Data Extraction and Filtering End-User Query Tool End User Presentation Tools Operational Stored in Normalized Relational Database Support transactions that represent daily operations (Not Query Friendly) Differences with DSS 3 Main Differences Time Span Granularity Dimensionality Operational DSS Time span Real time Historic Current transaction Short time frame Long time frame Specific Data facts Patterns Granularity
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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 the
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made. Through hydroponics more plants and crops can be created in a shorter amount of time. "Hydroponics is an excellent method of conducting research with controlled conditions of nutrient availability." The problem is that if the exact amount of minerals are not used the produce may have negative side effects or unwanted results. Through the research of hydroponics the less fortunate can produce their own crop while saving resources. A hydroponics garden may use only a fraction of the water a soil
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Data Mining On Medical Domain Smita Malik‚ Karishma Naik‚ Archa Ghodge‚ Shivani Gaunker Shree Rayeshwar Institute of Engineering & Information Technology Shiroda‚ Goa‚ India. Smilemalik777@gmail.com; naikkarishma39@gmail.com; archaghodge@gmail.com; shivanigaunker@gmail.com Abstract-The successful application of data mining in highly visible fields like retail‚ marketing & e-business have led to the popularity of its use in knowledge discovery in databases (KDD) in other industries
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Introduction to Data Mining Assignment 1 Ex1.1 what is data mining? (a) Is it another hype? Data mining is Knowledge extraction from data this 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. So‚ data mining definitely is not another hype it can be viewed as the result of the natural evolution of information technology. (b) Is it a simple transformation of technology developed
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Texas Minerals Inc. Audit Memo To: Daniel Alfredsson Date: Monday August31‚ 2013 Re: Audit Planning Memo for Texas Minerals This is not the first time audit of TX Minerals Inc. (TX). We have been auditing this firm for the past 20 years. This reduces the overall engagement risk. Our auditing firm should be pretty familiar with our client’s fertilizer business and the general control environment is well known to us as well. So‚ in theory‚ we should be able to rely on the internal control structure
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Wildcat Mining Recently there has been a dispute between the Munduruku Tribe and “wildcat miners”‚ in which several illegal miners had set up various mines on the Munduruku’s land in search of gold. To remove these miners on their land‚ the tribe’s leaders travelled to Brazil‚ demanding from the government to remove illegal miners on their territory. Unfortunately‚ a court action by the government could take years and years‚ thus the Munduruku Tribe decided to evict the illegal miners by themselves
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Data Mining DeMarcus Montgomery Dr. Janet Durgin CIS 500 June 9‚ 2013 Determine the benefits of data mining to the businesses when employing 1. Predictive analytics to understand the behavior of customers Predictive analytics is business intelligence technology that produces a predictive score for each customer or other organizational element. Assigning these predictive scores is the job of a predictive model‚ which has‚ in turn been trained over your data‚ learning from the experience
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March 2011 THAI MINING LEGISLATION 1. Laws Governing Exploration and Mining The principal law is the Minerals Act (1967)‚ last amended in 2002 by Minerals Act No. 5. The act governs onshore and offshore exploration‚ mineral production‚ mineral trading‚ oredressing‚ transport and export of minerals‚ other than petroleum. The Department of Primary Industry and Mining (“DPIM”) is empowered to administer the Minerals Act and to issue ministerial regulations. DPIM also provides technical assistance in
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