Association Rule Mining using Apriori Algorithm Ghanshyam Verma‚ Shruthi Varadhan Computer Technology Department KITS-Ramtek‚ Nagpur-441106 gs.verma@live.com shruthivaradhan@gmail.com Abstract— Data mining is the process that results in the discovery of new patterns in large data sets. Data mining involves six common classes of tasks: Anomaly detection‚ Association Rule Mining‚ clustering‚ classification‚ regression and summarization. Association rule learning is a popular and well researched
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EXECUTIVE SUMMARY The attached report analyzes the financial position of Semirara Mining Corporation. Semirara Mining Corporation is a publicly-listed mining company and a subsidiary of the DMCI Holdings‚ Inc. The company is engage in the business of coal mining and coal production. As of now‚ Semirara Mining Corporation is the only large-scale coal producer in the Philippines and is engaged in surface open cut mining of thermal coal from its Panian mine on Semirara Island‚ in the Antique Province
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Using Web Mining Preeti Sharma & Sanjay Kumar NIT Raipur‚ Raipur‚ Chattishgarh‚ India E-mail: preeti.nitu@gmail.com & Skumar.IT@nitrr.ac.in Abstract - Customer satisfaction is the key secret of success for all industries regardless of whether it is web enabled or not. This paper focuses the role of web mining in achieving a viable edge in business. Web mining is becoming the tool for success for those who adopt electronic means of operation for conducting their business. Web mining is the
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Knowledge-Based Visualization to Support Spatial Data Mining Gennady Andrienko and Natalia Andrienko GMD - German National Research Center for Information Technology Schloss Birlinghoven‚ Sankt-Augustin‚ D-53754 Germany gennady.andrienko@gmd.de http://allanon.gmd.de/and/ Abstract. Data mining methods are designed for revealing significant relationships and regularities in data collections. Regarding spatially referenced data‚ analysis by means of data mining can be aptly complemented by visual exploration
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Ministry over the coal mine rights. The Ministry of Coals had earlier (2010) considered keeping 10% of thickly forested areas in the “no go” zone and open others for mining after following the due clearance process. Prior to that the environment ministry had carried out a joint exercise with the coal ministry studying nine major coal mining areas. fields (Singrauli‚IB valley‚Mand Raigarh‚Sohagpur‚Talcher‚Vardha valley‚Hasdeo-Arand‚ North karanpura and West bokaro). The ministry classified these blocks
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Case StudyWhat Can Businesses Learn From Text Mining?Text mining is the discovery of patterns and relationships from large sets of unstructured data – the kind of data we generate in e-mails‚ phone conversations‚ blog postings‚ online customer surveys‚ and tweets. The mobile digital platform has amplified the explosion in digital information‚ with hundreds of millions of people calling‚ texting‚ searching‚ “apping” (using applications)‚ buying goods and writing billions of e-mails on the go.Consumers
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Text mining is the discovery of patterns and relationships from large sets of unstructured data—the kind of data we generate in e-mails‚ phone conversations‚ blog postings‚ online customer surveys‚ and tweets. The mobile digital platform has amplified the explosion in digital information‚ with hundreds of millions of people calling‚ texting‚ searching‚ “apping” (using applications)‚ buying goods‚ and writing billions of e-mails on the go. Consumers today are more than just consumers: they
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system is incomplete without a doctor and a patient because without them a healthcare system is nothing. Why Data Mining can Aid HealthCare? Before talking about that why Data Mining can Aid Healthcare‚ there is a need to define that What is Data Mining‚ Why It is useful and Why it is required. What is Data Mining? Data Mining is the method of searching data from a large database. Data Mining is a technique that is used when we have a large database which is to be searched by applying some methods of
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choosing this particular topic was to focus on privacy-preserving clustering that protects the underlying attribute values of objects subjected to clustering analysis. In doing so‚ the privacy of individuals’ data would be protected. In this age of data mining‚ we felt that working on data privacy was of paramount importance. We worked in a group of 3 on this and my role specifically was to design and implement the ‘K-means’ algorithm that clusters the data and forms the basis for the data transformation
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to measure them experimentally. This is because ores are mixtures of the required mineral and unwanted material‚ and‚ being mixtures‚ they have variable composition. Measurement of the yield from a particular ore body is extremely important in the mining and minerals industry because it determines whether extraction of the metal from that ore is profitable or not. Whenever a new ore body is found‚ samples must be analyzed to determine the likely yield of the metal from it‚ and hence to decide whether
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