tools that are used for making critical business decisions are DSS, DDS, BI, Business Analytics and Predictive Analytics systems. The concepts/ systems mentioned assist management in the major decision-making processes by providing crucial operational data in comprehensible formats for monitoring/ reviewing and analyzing. Making the best decisions regarding business operations determine the success or failure of the company and ensures that all business strategies are implemented and effective. In this
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feature selection using data mining techniques P. Ravisankar a, V. Ravi a,⁎, G. Raghava Rao a, I. Bose b a b Institute for Development and Research in Banking Technology, Castle Hills Road #1, Masab Tank, Hyderabad 500 057, AP, India School of Business, The University of Hong Kong, Pokfulam Road, Hong Kong a r t i c l e i n f o a b s t r a c t Recently, high profile cases of financial statement fraud have been dominating the news. This paper uses data mining techniques such as Multilayer
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evolves and adjust to consumers for direct advertising efforts. 2. Cloud Computing (I-cloud/Verizon Cloud) – cloud computing affects the way that a company may store its data, software integration, and back-up and recovery. Clouds allow data storage and back and recovery in a cost efficient manner. Businesses are outsourcing data storage to third parties using cloud technology. Since cloud technology is still fairly new there are some security concerns that will be addressed and corrected overtime
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[BI-PROJECT REPORT] April 13, 2014 DATA MINING Analysis of Bike sharing dataset April 13, 2014 Group 007 MIS 6324 1 [BI-PROJECT REPORT] April 13, 2014 Project Report for Analysis of bike sharing dataset MIS-6324 Intro. to business intelligence software and techniques Prepared by Group Name Group007 Group Members Rohith Raj Abhay Joshi Sai Karan Jahnavi Papanaboina Under the guidance of Professor Kelly Slaughter, PhD Clinical Professor Information Systems University
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him/her to decide which product to buy. For a product manufacturer, the comparison enables it to easily gather marketing intelligence. This tool shows the features of a product along with their polarity on a bar graph. This tool uses language pattern mining and it extracts product features from the reviews of the format containing Pros and Cons of a particular product. Experimental results show that the technique is highly effective as it summarizes product reviews given by different customers. It visualizes
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applicability in case of its previous history. For Confidentiality-preservation of the data, the concept of counterweight providing reliable party is used. Keywords- Confidentiality-preservation, Naïve Bayes, distributed databases, partition. I. INTRODUCTION In current years, There has been an advancement of computing and
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A DATA MINING APPLICATION TO PREDICT THE INCOME LOSS, ITS EFFECT TO THE DAILY LIVES OF SELECTED JEEPNEY DRIVERS (PISTON-Lagro) DUE TO FARE DISCOUNTS A Thesis Proposal Presented to the Faculty of the College of Engineering and Technology New Era University In Partial Fulfillment of the Requirements for the Degree Computer Science By: JOMAR DAVE E. ASUNCION 2013 APPROVAL SHEET This thesis proposal titled “A DATA MINING APPLICATION TO PREDICT THE INCOME LOSS, ITS EFFECT TO
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Austin, TX 78705 August 31st, 2014 Dear Recruiting Manager, I am very interested in the Software Data Analyst position at GE. Currently, I am a graduate student at Mccombs School of Business majoring in business analytics. I believe my previous experience in consulting and leadership roles have prepared me well for this position. Prior to attending
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thereby continuously meet the changing demands of customers and the market place. Extensive planning by all concerned depts. viz production, marketing and operations is involved in designing a cost effective and result oriented supply chain. Historical data about consumer behavior is used to forecast demands on a weekly basis. Production planning based on long term forecasting is futile in present dynamic markets and hence the demands forecasts are continuously reviewed and discussed with production,
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recommender system research. In this paper, we propose a new personalized recommendation framework by leveraging and enhancing overlapping community concepts from complex network analysis literature and developing a time-weighted association rule mining method. Experiment results show that our proposed approach outperforms several existing methods in recommendation precision and diversity. Keywords: personalized recommendation; overlapping community; time-weighted association rules; user interests
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