INTERNATIONAL INSTITUTE OF PROFESSIONAL STUDIES DEVI AHILYA VISHWA VIDHYALAYA‚ INDORE [pic] “DBMS PROJECT HOTEL MANAGEMENT” MBA 3rd SEM Guided By: Submitted By: Dr. Priti Singh VARUN RAO(FT-2K9-58) HOTEL MANAGEMENT SYSTEM INTRODUCTION The main aim of the entire activity is to automate the process of day to day activities of Hotel like Room activities‚ Admission of a New Customer‚ Assign a room according to Customer’s demand‚ checkout of a computer and releasing
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Use of Data Mining in Fraud Detection Focus on ACL Hofstra University Abstract This paper explore how business data mining software are used in fraud detection. In the paper‚ we discuss the fraud‚ fraud types and cost of fraud. In order to reduce the cost of fraud‚ companies can use data mining to detect the fraud. There are two methods: focus on all transaction data and focus on particular risks. There are several data mining software on the market‚ we introduce seven
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will win is 60% and above.” Null Hypothesis “If X makes the first move then the probability of the player with X will win is less than 60%.” Data Collection and Preparation To prove or refute the hypothesis‚ data has to be collected. As we all know this step requires a great amount of time and effort. Also in order to build an effective model a data mining algorithm must be presented with a few hundred or few thousands relevant/applicable records. As mentioned above there are thousands of winning
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Department of Computer Science Database and Data Mining‚ COS 514 Dr. Chi Shen Homework No. 8‚ Chapter 13‚ Aklilu Shiketa Q13. 3 Cosmetic Purchases Consider the following Data on Cosmetics Purchases in Binary Matrix Form a) Select several values in the matrix and explain their meaning. Value Cell Meaning 0 For example‚ Row 1‚ Column2 At transaction #1 bag was not purchased. (shows absence of Bag in the transaction) 1 Row 10‚ column (2 and 3) “If a Bag is purchased‚ a Blush is also purchased
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Overview: Chapter 2 Data Mining for Business Intelligence Shmueli‚ Patel & Bruce Core Ideas in Data Mining Classification Prediction Association Rules Data Reduction Data Visualization and exploration Two types of methods: Supervised and Unsupervised learning Supervised Learning Goal: Predict a single “target” or “outcome” variable Training data from which the algorithm “learns” – value of the outcome of interest is known Apply to test data where value is not known and will be predicted
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Tata Motors – India aquisation of Daewoo Commercial Vehicles Company- Korea The case examines the first-ever overseas acquisition by an Indian automobile company. It gives a details of the acquisition of Daewoo Commercial Vehicles plant by Tata Motors‚ world’s sixth largest commercial vehicle manufacturer. Daewoo Commercial Vehicles Company (DWCV) had an installed capacity of 20‚000 vehicles from a state-of-the-art plant built in 1995. Produced more than 90 truck models in the heavy commercial
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2.1 Assuming that data mining techniques are to be used in the following cases‚ identify whether the task required is supervised or unsupervised learning. a. Supervised-Deciding whether to issue a loan to an applicant based on demographic and financial data (with reference to a database of similar data on prior customers). b. Unsupervised-In an online bookstore‚ making recommendations to customers concerning additional items to buy based on the buying patterns in prior transactions. c. Supervised-Identifying
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XXXVII Chapter 626 SECTION 9743 INSURANCE INSURANCE FIELD Claim settlement practices relating REPRESENTATIVES AND to motor vehicle insurance. OPERATIONS Entire Chapter 626.9743 Claim settlement practices relating to motor vehicle insurance.— (1) This section shall apply to the adjustment and settlement of personal and commercial motor vehicle insurance claims. (2) An insurer may not‚ when liability and damages owed under the policy are reasonably clear‚ recommend that a third-party
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DATA MINING FOR POTENTIAL CUSTOMERS: East – West Airlines/Telcon Jermaine Paul 12/12/2013 BUSINESS PROBLEM East-West Airlines (EA) is entering into partnership with the cellular service provider‚ Telcon‚ by marketing their service through direct mail. In order to achieve this‚ EA dataset is provided to categorize their customers to identify which ones would be likely to purchase Telcon’s services through direct mail. If the accurate categorization is done the partnership will save
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Data Mining Project on IMDB website ABSTRACT The Internet Movie Database (IMDb) is an online database of information related to movies‚ television shows‚ stars‚ etc. We chose to do our project from 2008 to 2011 year’s movie database. We extracted data like Movie‚ Director‚ Star‚ Image Url‚ Studio from the IMDb website. For this extraction of data we used a tool named Mozenda. After the data extraction‚ the data was analyzed. For a particular star‚ his/her movie‚ director‚ studio with whom the
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