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Relevant bibliographies by topics / Data mining Case studies

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Dissertations / Theses

Academic literature on the topic 'Data mining Case studies'

Author: Grafiati

Published: 10 December 2022

Last updated: 29 January 2023

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Dissertations / Theses on the topic "Data mining Case studies"

1

Xu, Jie. "MINING STATIC AND DYNAMIC STRUCTURAL PATTERNS IN NETWORKS FOR KNOWLEDGE MANAGEMENT: A COMPUTATIONAL FRAMEWORK AND CASE STUDIES." Diss., Tucson, Arizona : University of Arizona, 2005. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu%5Fetd%5F1151%5F1%5Fm.pdf&type=application/pdf.

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2

Ben, Nasr Sana. "Mining and modeling variability from natural language documents : two case studies." Thesis, Rennes 1, 2016. http://www.theses.fr/2016REN1S013/document.

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L'analyse du domaine vise à identifier et organiser les caractéristiques communes et variables dans un domaine. Dans la pratique, le coût initial et le niveau d'effort manuel associés à cette analyse constituent un obstacle important pour son adoption par de nombreuses organisations qui ne peuvent en bénéficier. La contribution générale de cette thèse consiste à adopter et exploiter des techniques de traitement automatique du langage naturel et d'exploration de données pour automatiquement extraire et modéliser les connaissances relatives à la variabilité à partir de documents informels. L'enj

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3

Madani, Farshad. "Opportunity Identification for New Product Planning: Ontological Semantic Patent Classification." PDXScholar, 2018. https://pdxscholar.library.pdx.edu/open_access_etds/4232.

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Intelligence tools have been developed and applied widely in many different areas in engineering, business and management. Many commercialized tools for business intelligence are available in the market. However, no practically useful tools for technology intelligence are available at this time, and very little academic research in technology intelligence methods has been conducted to date. Patent databases are the most important data source for technology intelligence tools, but patents inherently contain unstructured data. Consequently, extracting text data from patent databases, converting

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4

Šenovský, Jakub. "Dolování z dat v jazyce Python." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2017. http://www.nusl.cz/ntk/nusl-363895.

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The main goal of this thesis was to get acquainted with the phases of data mining, with the support of the programming languages Python and R in the field of data mining and demonstration of their use in two case studies. The comparison of these languages in the field of data mining is also included. The data preprocessing phase and the mining algorithms for classification, prediction and clustering are described here. There are illustrated the most significant libraries for Python and R. In the first case study, work with time series was demonstrated using the ARIMA model and Neural Networks

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5

Pena, Isis. "Utility-based data mining: An anthropometric case study." Thesis, University of Ottawa (Canada), 2008. http://hdl.handle.net/10393/27723.

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One of the most important challenges for the apparel industry is to produce garments that fit the population properly. In order to achieve this objective, it is crucial to understand the typical profile of consumer's bodies. In this work, we aim to identify the typical consumer from the virtual tailor's perspective. To this end, we perform clustering analysis on anthropometric and 3-D data to group the population into clothing sizes. Next, we perform multi-view relational classification to analyze the interplay of different body measurements within each size. In this study, we analyze three di

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6

Daley, Caitlin Marie. "Application of Data Mining Tools for Exploring Data: Yarn Quality Case Study." NCSU, 2008. http://www.lib.ncsu.edu/theses/available/etd-10292008-165755/.

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Businesses are constantly striving for a competitive edge in the economy, and data-driven decision making is crucial to achieve this goal. Four data mining tools, principal component analysis, cluster analysis, recursive partitioning, and discriminant analysis, were used to explore the major factors that contribute to ends down in a rotor spinning manufacturing process. Principal component analysis was used to explore the research question about whether the large number of cotton properties used to classify cotton could be reduced to a significant few. Cluster analysis was used to gain insight

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Ivanovskiy, Tim V. "Mining Medical Data in a Clinical Environment." Scholar Commons, 2006. http://scholarcommons.usf.edu/etd/3908.

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The availability of new treatments for a disease depends on the success of clinical trials. In order for a clinical trial to be successful and approved, medical researchers must first recruit patients with a specific set of conditions in order to test the effectiveness of the proposed treatment. In the past, the accrual process was tedious and time-consuming. Since accruals rely heavily on the ability of physicians and their staff to be familiar with the protocol eligibility criteria, candidates tend to be missed. This can result and has resulted in unsuccessful trials.A recent project at the

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8

桂宏胜 and Hongsheng Gui. "Data mining of post genome-wide association studies and next generation sequencing." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hdl.handle.net/10722/193431.

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9

Damle, Chaitanya. "Flood forecasting using time series data mining." [Tampa, Fla.] : University of South Florida, 2005. http://purl.fcla.edu/fcla/etd/SFE0001038.

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10

Haneuse, Sebastian J. P. A. "Ecological studies using supplemental case-control data /." Thesis, Connect to this title online; UW restricted, 2004. http://hdl.handle.net/1773/9595.

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