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Rozprawy doktorskie na temat „Data mining management”

Autor: Grafiati

Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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1

Adderly, Darryl M. "Data mining meets e-commerce using data mining to improve customer relationship management /." [Gainesville, Fla.]: University of Florida, 2002. http://purl.fcla.edu/fcla/etd/UFE0000500.

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Tong, Suk-man Ivy. "Techniques in data stream mining." Click to view the E-thesis via HKUTO, 2005. http://sunzi.lib.hku.hk/hkuto/record/B34737376.

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Tong, Suk-man Ivy, and 湯淑敏. "Techniques in data stream mining." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2005. http://hub.hku.hk/bib/B34737376.

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Zou, Beibei 1974. "Data mining with relational database management systems." Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=82456.

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With the increasing demands of transforming raw data into information and knowledge, data mining becomes an important field to the discovery of useful information and hidden patterns in huge datasets. Both machine learning and database research have made major contributions to the field of data mining. However, there is still little effort made to improve the scalability of algorithms applied in data raining tasks. Scalability is crucial for data mining algorithms, since they have to handle large datasets quite often. In this thesis we take a step in this direction by extending a popula

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Ma, Xuesong 1975. "Data mining using relational database management system." Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=98757.

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With the wide availability of huge amounts of data and the imminent demands to transform the raw data into useful information and knowledge, data mining has become an important research field both in the database area and the machine learning areas. Data mining is defined as the process to solve problems by analyzing data already present in the database and discovering knowledge in the data. Database systems provide efficient data storage, fast access structures and a wide variety of indexing methods to speed up data retrieval. Machine learning provides theory support for most of the popular d

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6

Saad, Elmak. "Optimizing E-management Using Web data mining." Thesis, University of Huddersfield, 2018. http://eprints.hud.ac.uk/id/eprint/34540/.

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Today, one of the biggest challenges that E-management systems face is the explosive growth of operating data and to use this data to enhance services. Web usage mining has emerged as an important technique to provide useful management information from user's Web data. One of the areas where such information is needed is the Web-based academic digital libraries. A digital library (D-library) is an information resource system to store resources in digital format and provide access to users through the network. Academic libraries offer a huge amount of information resources, these information re

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Ahmad, Yasmeen. "Management, visualisation & mining of quantitative proteomics data." Thesis, University of Dundee, 2012. https://discovery.dundee.ac.uk/en/studentTheses/6ed071fc-e43b-410c-898d-50529dc298ce.

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Exponential data growth in life sciences demands cross discipline work that brings together computing and life sciences in a usable manner that can enhance knowledge and understanding in both fields. High throughput approaches, advances in instrumentation and overall complexity of mass spectrometry data have made it impossible for researchers to manually analyse data using existing market tools. By applying a user-centred approach to effectively capture domain knowledge and experience of biologists, this thesis has bridged the gap between computation and biology through software, PepTracker (h

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Zeng, Chunqiu. "Large Scale Data Mining for IT Service Management." FIU Digital Commons, 2016. http://digitalcommons.fiu.edu/etd/3051.

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More than ever, businesses heavily rely on IT service delivery to meet their current and frequently changing business requirements. Optimizing the quality of service delivery improves customer satisfaction and continues to be a critical driver for business growth. The routine maintenance procedure plays a key function in IT service management, which typically involves problem detection, determination and resolution for the service infrastructure. Many IT Service Providers adopt partial automation for incident diagnosis and resolution where the operation of the system administrators and automat

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Wang, Qing. "Intelligent Data Mining Techniques for Automatic Service Management." FIU Digital Commons, 2018. https://digitalcommons.fiu.edu/etd/3883.

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Today, as more and more industries are involved in the artificial intelligence era, all business enterprises constantly explore innovative ways to expand their outreach and fulfill the high requirements from customers, with the purpose of gaining a competitive advantage in the marketplace. However, the success of a business highly relies on its IT service. Value-creating activities of a business cannot be accomplished without solid and continuous delivery of IT services especially in the increasingly intricate and specialized world. Driven by both the growing complexity of IT environments and

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Chen, Hsinchun. "Knowledge Management Systems: A Text Mining Perspective." Knowledge Computing Corporation, 2001. http://hdl.handle.net/10150/106481.

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Artificial Intelligence Lab, Department of MIS, University of Arizona<br>This bookâ s purpose is to present a balanced and integrated view of what a Knowledge Management System (KMS) is. We first define Knowledge Management (KM) from various consulting and IT perspectives and then pay particular attention to new and emerging technologies that help promote this new field. In particular, we present a review of some key KMS sub-fields: search engines, data mining, and text mining. We hope to help readers better understand the emerging technologies behind knowledge management, i.e., Knowledge M

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Liao, ChenHan. "Transaction-filtering data mining and a predictive model for intelligent data management." Thesis, Cranfield University, 2008. http://dspace.lib.cranfield.ac.uk/handle/1826/7027.

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This thesis, first of all, proposes a new data mining paradigm (transaction-filtering association rule mining) addressing a time consumption issue caused by the repeated scans of original transaction databases in conventional associate rule mining algorithms. An in-memory transaction filter is designed to discard those infrequent items in the pruning steps. This filter is a data structure to be updated at the end of each iteration. The results based on an IBM benchmark show that an execution time reduction of 10% - 19% is achieved compared with the base case. Next, a data mining-based predicti

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Ur-Rahman, Nadeem. "Textual data mining applications for industrial knowledge management solutions." Thesis, Loughborough University, 2010. https://dspace.lboro.ac.uk/2134/6373.

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In recent years knowledge has become an important resource to enhance the business and many activities are required to manage these knowledge resources well and help companies to remain competitive within industrial environments. The data available in most industrial setups is complex in nature and multiple different data formats may be generated to track the progress of different projects either related to developing new products or providing better services to the customers. Knowledge Discovery from different databases requires considerable efforts and energies and data mining techniques ser

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Liu, Xiao, and Xiao Liu. "Health Data Analytics: Data and Text Mining Approaches for Pharmacovigilance." Diss., The University of Arizona, 2016. http://hdl.handle.net/10150/620913.

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Pharmacovigilance is defined as the science and activities relating to the detection, assessment, understanding, and prevention of adverse drug events (WHO 2004). Post-approval adverse drug events are a major health concern. They attribute to about 700,000 emergency department visits, 120,000 hospitalizations, and $75 billion in medical costs annually (Yang et al. 2014). However, certain adverse drug events are preventable if detected early. Timely and accurate pharmacovigilance in the post-approval period is an urgent goal of the public health system. The availability of various sources of h

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14

Rentzmann, René. "Text Mining im Customer Relationship Management /." Hamburg : Kovač, 2008. http://www.verlagdrkovac.de/978-3-8300-3510-7.htm.

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Palmerini, Paolo <1971&gt. "On performance of data mining: from algorithms to management systems for data exploration." Doctoral thesis, Università Ca' Foscari Venezia, 2004. http://hdl.handle.net/10579/299.

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II Data Mining (DM) è la disciplina che si occupa dell'estrazione di informazioni utili e non banali dall'immensa mole di dati che è possibile collezionare in vari campi della scienza e del mondo industriale e commerciale. Il suo relativamente recente sviluppo lascia ancora aperti molti problemi che la comunità scientifica è chiamata ad affrontare e risolvere. Vi è la necessità di nuove metodologie per estrarre informazioni pi significative dai dati, nuovi framework si rendono indispensabili per armonizzare tutti i passi del processo di mining, nuove soluzioni sono necessarie per il trattament

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16

Kusick, André. "Evaluation von Data Mining Systemen für das Customer Relationship Management : ein Verfahren zum experimentellen Vergleich von Data Mining Systemen /." Saarbrücken : VDM Verlag Dr. Müller, 2007. http://deposit.d-nb.de/cgi-bin/dokserv?id=3018416&prov=M&dok_var=1&dok_ext=htm.

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Nguyen, Duc-Cuong. "Flexible information management strategies in machine learning and data mining." Thesis, Cardiff University, 2004. http://orca.cf.ac.uk/55917/.

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In recent times, a number of data rnining and machine learning techniques have been applied successfully to discover useful knowledge from data. Of the available techniques, rule induction and data clustering are two of the most useful and popular. Knowledge discovered from rule induction techniques in the form of If-Then rules is easy for users to understand and verify, and can be employed as classification or prediction models. Data clustering techniques are used to explore irregularities in the data distribution. Although rule induction and data clustering techniques are applied successfull

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Nguyen, Ngoc Buu Cat. "Data Mining in Knowledge Management Processes: Developing an Implementing Framework." Thesis, Umeå universitet, Institutionen för informatik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-149668.

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Analyzing a huge amount of data becomes a tricky challenge and an opportunity for data miners and businessmen today. Knowledge management processes can deal with big knowledge source to find tacit intelligence making businesses more agile and effective. Data mining is a powerful tool working with big data to create capabilities of forecasting and analysis. Yet there is a lack of research on where and how data mining can add value in knowledge management processes in organizations to maximize valuable knowledge for innovation and business management. The knowledge management processes of a psyc

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Qin, Xiao. "Sequential Data Mining and its Applications to Pharmacovigilance." Digital WPI, 2019. https://digitalcommons.wpi.edu/etd-dissertations/515.

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With the phenomenal growth of digital devices coupled with their ever-increasing capabilities of data generation and storage, sequential data is becoming more and more ubiquitous in a wide spectrum of application scenarios. There are various embodiments of sequential data such as temporal database, time series and text (word sequence) where the first one is synchronous over time and the latter two often generated in an asynchronous fashion. In order to derive precious insights, it is critical to learn and understand the behavior dynamics as well as the causality relationships across sequences.

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Thun, Julia, and Rebin Kadouri. "Automating debugging through data mining." Thesis, KTH, Data- och elektroteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-203244.

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Contemporary technological systems generate massive quantities of log messages. These messages can be stored, searched and visualized efficiently using log management and analysis tools. The analysis of log messages offer insights into system behavior such as performance, server status and execution faults in web applications. iStone AB wants to explore the possibility to automate their debugging process. Since iStone does most parts of their debugging manually, it takes time to find errors within the system. The aim was therefore to find different solutions to reduce the time it takes to debu

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21

Avena, Anna. "Tecniche di data mining applicate alla decodifica di dati neurali." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/14800/.

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Gli studi sulla decodifica dell'attività neuronale permettono di mappare gli impulsi elettrici della corteccia cerebrale in segnali da inviare a determinati dispositivi per poterli monitorare. È su questo tema che la ricerca scientifica si sta concentrando, al fine di aiutare le persone affette da gravi lesioni fisiche ad ottenere un maggiore grado di autonomia nelle piccole azioni di tutti i giorni. In questo elaborato, sono stati analizzati dati derivanti da attività neuronali raccolti da esperimenti effettuati su primati non umani, eseguiti dal gruppo di ricerca della professoressa Patrizi

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Vahedian, Khezerlou Amin. "Mining big mobility data for large urban event analytics." Diss., University of Iowa, 2019. https://ir.uiowa.edu/etd/7039.

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This thesis seeks to formulate concepts and develop methods that facilitate the mining of urban big mobility data. Specifically, the aim of the formulations and developed methods is to identify and predict certain events that occur as a result of urban mobility. This thesis, studies unexpected gathering and dispersal events. A Gathering event is the process of an unusually large number of moving objects (e.g. taxi) arriving at the same area within a short period of time. It is important for city management to identify emerging gathering events which might cause public safety or sustainability

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Nicholson, Scott, and Jeffrey M. Stanton. "Gaining Strategic Advantage through Bibliomining: Data Mining for Management Decisions in Corporate, Special, Digital, and Traditional Libraries." Hershey, PA: Idea Group Publishing, 2003. http://hdl.handle.net/10150/106383.

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Library and information services in corporations, schools, universities, and communities capture information about their users, circulation history, resources in the collection, and search patterns (Koenig, 1985). Unfortunately, few libraries have taken advantage of these data as a way to improve customer service, manage acquisition budgets, or influence strategic decision-making about uses of information in their organizations. In this chapter, we present a global view of the data generated in libraries and the variety of decisions that those data can inform. We describe ways in which library

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Fang, Cheng-Hung. "Application for data mining in manufacturing databases." Ohio : Ohio University, 1996. http://www.ohiolink.edu/etd/view.cgi?ohiou1178653424.

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Chan, Francis. "Knowledge management in Naval Sea Systems Command : a structure for performance driven knowledge management initiative." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2002. http://library.nps.navy.mil/uhtbin/hyperion-image/02sep%5FChan.pdf.

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Thesis (M.S. in Product Development)--Naval Postgraduate School, September 2002.<br>Thesis advisor(s): Mark E. Nissen, Donald H. Steinbrecher. Includes bibliographical references (p. 113-117). Also available online.

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Carlsson, Emil. "Mining Git Repositories : An introduction to repository mining." Thesis, Linnéuniversitetet, Institutionen för datavetenskap (DV), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-27742.

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When performing an analysis of the evolution of software quality and software metrics,there is a need to get access to as many versions of the source code as possible. There isa lack of research on how data or source code can be extracted from the source controlmanagement system Git. This thesis explores different possibilities to resolve thisproblem. Lately, there has been a boom in usage of the version control system Git. Githubalone hosts about 6,100,000 projects. Some well known projects and organizations thatuse Git are Linux, WordPress, and Facebook. Even with these figures and clients,

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Ding, Yichen. "Mining Spatio-Temporal Reachable Regions over Massive Trajectory Data." Digital WPI, 2017. https://digitalcommons.wpi.edu/etd-theses/211.

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Mining spatio-temporal reachable regions aims to find a set of road segments from massive trajectory data, that are reachable from a user-specified location and within a given temporal period. Accurately extracting such spatio-temporal reachable area is vital in many urban applications, e.g., (i) location-based recommendation, (ii) location-based advertising, and (iii) business coverage analysis. The traditional approach of answering such queries essentially performs a distance-based range query over the given road network, which have two main drawbacks: (i) it only works with the physical tra

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Gleue, Christoph [Verfasser]. "Data Mining und Big Data Analytics : semantische Suche, Prognose und Entscheidungsunterstützung mit Künstlichen Neuronalen Netzen / Christoph Gleue." Hannover : Gottfried Wilhelm Leibniz Universität Hannover, 2019. http://d-nb.info/1188406469/34.

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Neis, Jan [Verfasser]. "Analyse der Produktportfoliokomplexität unter Anwendung von Verfahren des Data Mining / Jan Neis." Aachen : Shaker, 2015. http://d-nb.info/1081885009/34.

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Roach, John. "DESIGN OF A CONFIGURATIONAND MANAGEMENT TOOL FORINSTRUMENTATION NETWORKS." International Foundation for Telemetering, 2007. http://hdl.handle.net/10150/604484.

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ITC/USA 2007 Conference Proceedings / The Forty-Third Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2007 / Riviera Hotel & Convention Center, Las Vegas, Nevada<br>The development of network-based data acquisition systems has resulted in a new architecture for supporting flight instrumentation that has the potential to revolutionize the way we test our aircraft. However, the inherent capability and flexibility in a networked test architecture can only be realized by the flight engineer if a sufficiently powerful toolset is available that can configure

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TICONA, WILFREDO MAMANI. "STUDY OF DATA MINING METHODS APPLIED TO THE FINANCIAL MANAGEMENT OF MUNICIPALITIES." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2013. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=35344@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>PROGRAMA DE EXCELENCIA ACADEMICA<br>Os impostos arrecadados pelas prefeituras são revertidos para o bem comum, para investimentos (tais como infraestrutura) e custeio de bens e serviços públicos, como saúde, segurança e educação. A previsão de valores futuros a serem arrecadados é uma das tarefas que as prefeituras têm como desafio. Essa é uma tarefa importante, pois as informações obtidas das previsões são valiosas para dar apoio à decisão com relação ao planejamento estratégi

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Emerson, Daniel. "A data mining driven crash risk profiling method for road asset management." Thesis, Queensland University of Technology, 2013. https://eprints.qut.edu.au/61863/1/Daniel_Emerson_Thesis.pdf.

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This thesis takes a new data mining approach for analyzing road/crash data by developing models for the whole road network and generating a crash risk profile. Roads with an elevated crash risk due to road surface friction deficit are identified. The regression tree model, predicting road segment crash rate, is applied in a novel deployment coined regression tree extrapolation that produces a skid resistance/crash rate curve. Using extrapolation allows the method to be applied across the network and cope with the high proportion of missing road surface friction values. This risk profiling

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Kudowor, Andrew Yao Tete. "Subsurface data management and volume estimation : techniques, procedures, and concepts." Thesis, University of Newcastle Upon Tyne, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.285787.

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Meng, Changping, and 蒙昌平. "Discovering meta-paths in large knowledge bases." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/209504.

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A knowledge base, such as Yago or DBpedia, can be modeled as a large graph with nodes and edges annotated with class and relationship labels. Recent work has studied how to make use of these rich information sources. In particular, meta-paths, which represent sequences of node classes and edge types between two nodes in a knowledge base, have been proposed for such tasks as information retrieval, decision making, and product recommendation. Current methods assume meta-paths are found by domain experts. However, in a large and complex knowledge base, retrieving meta-paths manually can be tediou

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Fair, Martin Lynn. "Geo-demographic analysis in support of the United States Army Reserve (USAR) Unit Positioning and Quality Assessment Model (UPQUAM)." Thesis, Monterey California. Naval Postgraduate School, 2004. http://hdl.handle.net/10945/1592.

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Manning United States Army Reserve (USAR) units are fundamentally different from manning Regular Army (RA) units. A soldier assigned to a USAR unit must live within 75 miles or 90 minutes commute of his Reserve Center (RC). This makes reserve unit positioning a key factor in the ability to recruit to fill the unit. This thesis automates, documents, reconciles, and assembles data on over 30,000 ZIP Codes, over 800 RCs, and over 260 Military Occupational Specialties (MOSs), drawing on and integrating over a dozen disparate databases. This effort produces a single data file with demographic, voca

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Robey, John L. Odell Christopher W. "Facilitating decision making, re-use and collaboration a knowledge management approach to acquisition program self-awareness /." Monterey, Calif. : Naval Postgraduate School, 2009. http://edocs.nps.edu/npspubs/scholarly/theses/2009/Jun/09Jun%5FRobey.pdf.

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Thesis (M.S. in Systems Technology)--Naval Postgraduate School, June 2009 by John L. Robey. Thesis (M.S. in Information Technology Management)--Naval Postgraduate School, June 2009 by Christopher W. Odell.<br>Thesis Advisor(s): Gallup, Shelley P. "June 2009." Description based on title screen as viewed on 13 July 2009. Author(s) subject terms: Defense Acquisition System, Knowledge Management (KM), Open Architecture (OA), Capability Portfolio Management (CPM), Business Intelligence (BI), Maritime Domain Awareness (MDA), Data mining, Text Mining, Data Visualization. Includes bibliographical refe

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Ivkovic, Sasha. "Visual grouping of association rules for hypotheses suggestion." Thesis, The Author [Mt. Helen, Vic.] :, 2003. http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/41572.

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The study descibes a KDD method that is being used by non-technical experts with mimimal training to discover and interpret patterns that they find useful for their role within their organisations.<br>Master of Information Technology

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Hu, Guei-Hau, and 胡桂豪. "Applying Data Mining to Detect Earning Management." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/43045083705339701993.

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碩士<br>中國文化大學<br>會計學系<br>101<br>Many studies focus on whether companies faithfully present their economics sub-stance in the financial report. Earning management is one of those topics that manage-ment manipulates earnings to serve certain purpose. In recent researches, data mining has been applied to business activities exten-sively. In the present study, the three steps model has been built to detect earnings management levels. First, applied step wise regression and Random Forest algorithm to the sample selection. Second, structure data mining models by using MLP、SVM and LS-SVM techniques. A

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Wang, Hsiu-Yu, and 王秀育. "Applying Data Mining to Telecom Churn Management." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/26644603560712631221.

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碩士<br>國立中正大學<br>資訊管理學系<br>91<br>In Taiwan, the wireless telecommunication market was opened to the private enterprises since 1997. As the deregulation and great advance of new technologies, the competition in wireless telecommunication industry is getting severe. Accordingly, churn prediction and management have become of great concern to the mobile operators. Mobile operators wish to retain their subscribers and satisfy their needs. Hence, they need to predict the possible churners and then utilize the limited resources to retain those customers. In response to the difficulty of churner predi

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Huang, I.-Lin, and 黃奕霖. "ISP Customer Relationship Management using Visualization Data Mining." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/25927320847965198853.

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碩士<br>國立高雄第一科技大學<br>資訊管理所<br>92<br>Telecommunication liberalization in Taiwan attracts a lot of Internet Service Providers (ISPs) to invest into the internet service market. The influence of the ISP industry has become more and more competitive. To satisfy customers’ need in such competitive ISP market, the ISPs must raise the network frequently wide demand and lower the price. The cutting price strategy causes customers to change the ISPs frequently. Therefore, it is important for ISPs to know how to keep their customers’loyalty in the long run. The customer satisfaction is an important str

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Hsu, Yao-wen, and 許耀文. "Data Mining of Pavement Maintenance & Rehabilitation Management." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/fg5p58.

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碩士<br>國立中央大學<br>土木工程研究所<br>96<br>The process of collecting pavement data has been evolving with advances in technology, thus generating huge amounts of data by both objective and subjective methods to be stored in pavement management systems (PMS) databases. The rapid size increases of these databases presents a challenge for state agencies, as they attempt to understand and take advantage of the data to support pavement maintenance and rehabilitation (M&R) decisions. Data mining is an interdisciplinary research area spanning several disciplines such as database systems, machine learning, inte

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Chen, Wei-Chung, and 陳威仲. "Earnings Management Detection Models Using Data Mining Approach." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/47pn25.

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碩士<br>中國文化大學<br>會計學系<br>105<br>Companies release and reliability financial statements and management manipulated discretional accruals earnings management of arbitral accruals has been a major issue for many years. Past literature on the discretional accruals earnings management are all using traditional regression model, in recent years there have been many scholars have applied data mining methods for discretional earnings management research. Therefore, this study data mining methods neural network and Chi-Square Automatic Interaction Detector for Decision trees to predict, hoping to identi

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CHEN, HAO-YU, and 陳皓昱. "Effective Earning Management Prediction Models Using Data Mining." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/339kb3.

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碩士<br>中國文化大學<br>會計學系<br>107<br>The selection data of this study comes from the Taiwan Economic News (TEJ). The selection period is from Taiwan to the electronic industry in 2009-2017. In the past, scholars used the regression model as an analysis. In recent years, the accuracy of data mining by scholars is relative to that of data mining. In the past, it has improved. Therefore, this study uses the support vector machine as the first-stage variable screening, selecting the variables that are more important for earnings management, and then using the decision tree CART, decision tree CHAID. As

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Gahlaut, Himanshu. "Prevention of Malicious Transactions in Database Management Systems." Thesis, 2009. http://ethesis.nitrkl.ac.in/1313/1/Himanshu_Gahlaut__10506028__Thesis.pdf.

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Database Management Systems are a key component in the information infrastructure of most organizations nowadays so security of DBMS has become more crucial. Several mechanisms needed to protect data, such as authentication, user privileges, encryption, and auditing, have been implemented in commercial DBMS. But still there are some ways through which systems may be affected by malicious transactions. Our definition of malicious transaction is that transaction which the user is not authorized to perform. Even the sequence of the operations in the transaction is not to be violated. Existing int

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Sarkas, Nikolaos. "Querying, Exploring and Mining the Extended Document." Thesis, 2011. http://hdl.handle.net/1807/29857.

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The evolution of the Web into an interactive medium that encourages active user engagement has ignited a huge increase in the amount, complexity and diversity of available textual data. This evolution forces us to re-evaluate our view of documents as simple pieces of text and of document collections as immutable and isolated. Extended documents published in the context of blogs, micro-blogs, on-line social networks, customer feedback portals, can be associated with a wealth of meta-data in addition to their textual component: tags, links, sentiment, entities mentioned in text, etc. Collections

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Tsai, Wei-hsin, and 蔡維欣. "The Approved Data Mining Process for Customer Relationship Management." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/36142286717902893609.

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碩士<br>輔仁大學<br>應用統計學研究所<br>91<br>Customer is the most fundamental and direct element of business activities. By the progress of informational technology, customers can now reach plentiful product information through various channels. It is then only by customer relationship management: to understand customers, to produce customized products, to maintain customers’ loyalty, and to keep good interaction with customers, can enterprises maintain operating and gain profit. And by customer data analysis, to understand customer consuming behavior and preference, can enterprises raise the loyalty of cu

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Hsu, Hei-ting, and 許惠婷. "Applying Data Mining Approach in an Outsourcing Management Environment." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/01056354525853763583.

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碩士<br>國立臺灣科技大學<br>工業管理系<br>93<br>Outsourcing is a strategy for the enterprise to maintain the competition ability. This research tends to apply data mining technology to support the outsourcing management for Chung-Shan Institute of Science and Technology (CSIST) the purpose of this research is to find out the rules or patterns that were hided in the supplier data by using data mining, and then uses the mining results to predict the supplier’s performance to assist CSIST to manage the outsourcing supplier. There are several phases in this research. One was to define the performance attributes

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Chang, Keng-Wei, and 張耕維. "A Study on Data Mining for Firewall Policy Management." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/92525909164967433063.

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碩士<br>國立臺灣大學<br>工程科學及海洋工程學研究所<br>95<br>Motivation: Firewall system is the most popular network security mechanism for enterprises. Due to the dynamic feature of network environment, firewall policy rules must be constantly revised and adapted to assure the security of intranet. The problem we address is how to apply data mining technology for analyzing firewall logs and assisting network administrators to improve firewall efficiency and to safeguard the network. Method: We apply association rule mining to analyze network logs and detect anomalous behaviors, such as connections those shown freq

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Fan, Shiu-Hao, and 范修豪. "Activity Mining and Dynamic Data Management in Mobile Environments." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/93235269935614716722.

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碩士<br>國立東華大學<br>資訊工程學系<br>94<br>With the popularity of mobile computing, mobile data management is becoming the one of the important research topic. We propose a new idea of user activity for characterizing complex and changing behavior patterns of mobile users. The type of each individual activity may not be the same. It can be composed of movement pattern, service pattern, or the hybrid pattern with both location movement and service requests. Distinctive types of activities can be combined into a larger activity. Hence, the activity concept provides a more precise, rich, and detail descrip

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Wang, Shih-Chao, and 王世昭. "The application of data mining on customer relationship management." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/51619510113556887007.

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碩士<br>國防大學理工學院<br>資訊科學碩士班<br>99<br>CRM（Customer Relationship Management）is an important subject for an enterprise to build up a competitive advantage in recent years. CRM means to manage the relationships between enterprises and customers. Churn prediction is a popular issue in the field of CRM. By using customer information, data mining technology can be applied to analyze and predict the possible churners. Then, the enterprise can plan some effective strategies to retain customers for more profits. For the customer churn prediction issue, this thesis applies the feature selection methods, th

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