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1
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, thereare very few tools able to perform data extraction from Git repositories. A pre-studyshowed that there is a lack of standardization on how to share mining results, and themethods used to obtain them. There are several tools available for older version control systems, such as concurrentversions system (CVS), but few for Git. The examined repository mining applicationsfor Git are either poorly documented; or were built to be very purpose-specific to theproject for which they were designed. This thesis compiles a list of general issues encountered when using repositorymining as a tool for data gathering. A selection of existing repository mining tools wereevaluated towards a set of prerequisite criteria. The end result of this evaluation is thecreation of a new repository mining tool called Doris. This tool also includes a smallcode metrics analysis library to show how it can be extended.
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Schieber, Andreas, and Paul Kruse. "Idea Mining." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-140499.
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Motiviert durch den Erfolg des Web 2.0 und Social Media in vielen Bereichen des öffentlichen Lebens und der damit verbundenen Open-Innovation-Bewegung, die Kunden aktiv in den Innovationsprozess einbezieht, schlägt dieser Beitrag eine Integration von Wissensmanagement und Text Mining zur Verbesserung dieses Innovationsprozesses vor. Durch den beschriebenen Ansatz werden Kunden nicht nur motiviert, ihre Ideen und Bedürfnisse auf webbasierten Kommunikationsplattformen preiszugeben, sondern die entstehenden, textbasierten Daten können automatisiert ausgewertet und zur zielgerichteten und zeitnahen Weiterentwicklung der Produkte eingesetzt werden. Anhand zweier Anwendungsszenarien aus der Praxis werden das resultierende Prozessmodell dargestellt und dessen Potenziale veranschaulicht.
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Mrázek, Michal. "Data mining." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2019. http://www.nusl.cz/ntk/nusl-400441.
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The aim of this master’s thesis is analysis of the multidimensional data. Three dimensionality reduction algorithms are introduced. It is shown how to manipulate with text documents using basic methods of natural language processing. The goal of the practical part of the thesis is to process real-world data from the internet forum. Posted messages are transformed to the numerical representation, then to two-dimensional space and visualized. Later on, topics of the messages are discovered. In the last part, a few selected algorithms are compared.
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Zúñiga, Larrondo Diego, and Fuentealba Fernando Ruiz. "Provetec mining." Tesis, Universidad de Chile, 2015. http://repositorio.uchile.cl/handle/2250/137210.
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Tesis para optar al grado de Magíster en AdministraciónDiego Zúñiga Larrondo [Parte I no autoriza acceso a texto completo de su documento ], Fernando Ruiz Fuentealba [Parte II no envía autorización para acceso a texto completo de su documento]
En Chile la industria minera es uno de los principales motores de la economía nacional, teniendo un gran nivel de consumidores de bienes y servicios, de igual forma su solvencia, estabilidad e inversión, lo resaltan como un mercado sumamente atractivo para proveedores de diferentes sectores. De igual forma las relaciones laborales, seguridad ocupacional y altos estándares de calidad, permiten metodologías en que los algunos proveedores puedan visualizar y resolver los requerimientos de la industria, obteniendo además márgenes positivos en los contratos adjudicados, sin perjuicio de lo anterior existen barreras de entradas con fuertes restricciones de ingresos limitando el acceso a la competencia de empresas sin dichos niveles. Cabe desatacar que dentro de un proyecto minero, la etapa de construcción involucra altos niveles de inversión en obras, generando una fuerte demanda a la industria de la construcción, siendo esta una oportunidad de desarrollo económico y productivo. En general los megos proyectos - mineros cuentan con características similares, como por ejemplo: Sondaje Movimiento de Tierra Masivo Obras de Ingeniera Obras de Infraestructura Obras sanitarias Según Cochilco1, sobre las bases de los antecedentes de cada proyecto de fuentes públicas, nuestros país cuenta con una cartera de proyectos compuesta por 53 proyectos mayores de 90 millones de dólares de inversión, que suman un requerimiento de inversión de 104,8 mil millones de dólares, de los cuales se estima que el 16% ya ha sido gastado en proyectos antes del 2014. Y el 47% se desembolsaría entre 2014 y 2018, con un promedio anual cercano a los 10 mil millones de dólares. El restante 37% lo sería del 2019 en adelante. PROVETEC considera ampliar su core business creando la división prefabricados ofreciendo una solución integral en los requerimientos de obras civiles, participando en las diferentes actividades de la ruta crítica del negocio.
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Östlund, Jacob, and Kristian Kierkegaard. "Uranium Mining Industry : -A valuation of uranium mining companies." Thesis, Jönköping University, JIBS, Accounting and Finance, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-927.
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Background:
Over the last three years uranium prices have soard from US $14 per pound (lb) to the current price of US $120/lb and this rapid incline of the commodity have created a boom within the uranium prospecting and min-ing industry. There are currently 435 nuclear reactors all over the world and these reactors demand 180 millions of pounds of uranium each year to run at full production. Currently the uranium mining industry only sup-plies 110 million pounds of the demanded quantity. The remaining 70 mil-lion pounds are coming from secondary sources such as decommissioned nuclear warheads and other sources. Market estimations say that the sec-ondary sources will only cover the shortage up until around 2012 then primary sources have to supply almost the whole quantity demanded. These factors imply that some sort of analysis model for uranium mining companies would be needed.
Purpose:
The purpose of this report is to valuate three companies within the ura-nium industry and to establish if the current market value is coherent with the fundamental value of these companies. The authors will propose a valuation model that could be used when valuating companies within the uranium industry.
Method:
A qualitative method has been used in order to value three companies within the uranium mining business that are fairly large players on the market. The valuation of these companies is based upon a discounted cash flow analysis, a relative PV valuation and relative valuation. The compa-nies included in the report are corporations that are quoted at Toronto Stock Exchange and they have started mining uranium. Data have been collected through annual reports and the companies Internet pages. Other secondary information such as valuation theories has been collected from academic search engines and books on the subjects.
Conclusions:
The current market values of uranium mining companies are not coherent with the actual fundamental values according to the authors. Both funda-mental and a comparative approach could be used when valuing these companies and the most important part in the valuation is to try and fore-cast the commodity price and then to estimate the companies possible mining reserve/extractable resources.
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Vithal, Kadam Omkar. "Novel applications of Association Rule Mining- Data Stream Mining." AUT University, 2009. http://hdl.handle.net/10292/826.
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From the advent of association rule mining, it has become one of the most researched areas of data exploration schemes. In recent years, implementing association rule mining methods in extracting rules from a continuous flow of voluminous data, known as Data Stream has generated immense interest due to its emerging applications such as network-traffic analysis, sensor-network data analysis. For such typical kinds of application domains, the facility to process such enormous amount of stream data in a single pass is critical.
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Martínez, Aponte Humberto. "Obligations Regime of the Mining Concession (Mining rights system)." Derecho & Sociedad, 2015. http://repositorio.pucp.edu.pe/index/handle/123456789/117509.
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Mining concessions are subject to the fulfillment of liabilities by their owners based on ground for revocation, known as «expiration», as part of mining rights systems. The recent evolution of these liabilities and their focus as part of the conditions offered by the country for investment are analyzed by the author. To do this, the author conduct a review about the changes taken place in 1991 and 2008 mainly, as well as provides the elements to analyze the appropriateness of modifications or its flexibility. The tables used in the explanation constitutes a contribution, which were used by the author in conferences and due diligence for mining projects, as well as the consideration of both elements in the analysis of doctrine and real application of these concepts under the system of Peru.Las concesiones mineras están sujetas al cumplimiento de obligaciones por sus titulares, bajo causal de revocación, conocida como la «caducidad», enmarcadas en sistemas de amparo minero. La evolución reciente de estas obligaciones, así como enfocarlas como parte de las condiciones que ofrece el país para la inversión, son analizados por el autor. Para ello, realiza una revisión de las modificaciones ocurridas en 1991 y 2008 principalmente, así también proporciona los elementos para reflexionar sobre la conveniencia de nuevas modificaciones o de su flexibilización. Constituyen un aporte los cuadros empleados en la explicación, utilizados por el autor tanto en conferencias, como en due diligence en proyectos mineros; así como considerar en el análisis tanto elementos de doctrina, como de aplicación real deestos conceptos en el régimen del Perú.
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Madalane, Thembi. "The obligation to rehabilitate mining areas : post mining activities." Thesis, University of Limpopo (Turfloop Campus), 2012. http://hdl.handle.net/10386/905.
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Thesis (LLM) -- University of Limpopo, 2012The study focuses on rehabilitation, since absence of proper rehabilitation process result in indelible damage to the environment. South Africa, like many other countries, is faced with many environmental problems caused by mining. These problems are particularly caused by, inter alia, abandoned mining areas without rehabilitation, inadequate environmental impact assessment after closure, inadequate financial provision for rehabilitation, and lack of monitoring and aftercare system after post mine closure. The study found that many Companies ignore laws governing prospecting, extraction and rehabilitation. The main purpose of this research is to investigate and recommend guidelines in the rehabilitation process so as to instil respect for the environment. The study therefore recommended strict legislation relating to environmental protection against mining.
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Mahamaneerat, Wannapa Kay Shyu Chi-Ren. "Domain-concept mining an efficient on-demand data mining approach /." Diss., Columbia, Mo. : University of Missouri--Columbia, 2008. http://hdl.handle.net/10355/7195.
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Title from PDF of title page (University of Missouri--Columbia, viewed on February 24, 2010). The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file. Dissertation advisor: Dr. Chi-Ren Shyu. Vita. Includes bibliographical references.
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Bjørkelund, Eivind, and Thomas Hoberg Burnett. "Temporal Opinion Mining." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-18845.
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This project explores the possibilities in detecting changes in opinion over time. For this purpose, different techniques and algorithms in opinion mining have been studied and used as a theoretic foundation when developing strategies towards detecting changes in opinions.Different approaches to a system that detects and visualises changes in opinions have been proposed. These approaches include using machine learning techniques like the naiveBayes algorithm and opinion mining techniques based on SentiWordNet. Additionally,feature extraction techniques and the impact of burst detection have been studied.During this project, experiments have been carried out in order to test some of the techniques and algorithms. A data set containing hotel reviews and a prototype have beenbuilt for this purpose, allowing easy support for testing and validation. Results found high accuracy in opinion mining with the lexicon SentiWordNet, and the prototype can detect hotel features and possible reasons for changes in opinion. It can also show "good" and "bad" geographical areas based on hotel reviews.For commercial use, the prototype can help analyse the massive amount of hotel informa-tion published each day by customers, and can help hotel managers analyse their products. It can also be used as a more advanced hotel search engine where users can find extra information in a map user interface.
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Belin, Siderov Mitkov. "AUTONOMOUS MINING VEHICLE." Thesis, KTH, Industriell produktion, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-215965.
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van, der Aalst Wil M. P., Arya Adriansyah, Alves de Medeiros Ana Karla, Franco Arcieri, Thomas Baier, Tobias Blickle, Jagadeesh Chandra Bose R. P, et al. "Process Mining Manifesto." Springer, 2011. http://dx.doi.org/10.1007/978-3-642-28108-2_19.
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Process mining techniques are able to extract knowledge from event logs commonly available in today's information systems. These techniques provide new means to discover, monitor, and improve processes in a variety of application domains. There are two main drivers for the growing interest in process mining. On the one hand, more and more events are being recorded, thus, providing detailed information about the history of processes. On the other hand, there is a need to improve and support business processes in competitive and rapidly changing environments. This manifesto is created by the IEEE Task Force on Process Mining and aims to promote the topic of process mining. Moreover, by defining a set of guiding principles and listing important challenges, this manifesto hopes to serve as a guide for software developers, scientists, consultants, business managers, and end-users. The goal is to increase the maturity of process mining as a new tool to improve the (re)design, control, and support of operational business processes.
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Zhang, Minghua, and 張明華. "Sequence mining algorithms." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B44570119.
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Suwannaroj, Sujimarn. "Mining biological literature." Thesis, University of Sheffield, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.421163.
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Wang, Yi. "Dynamic Causal Mining." Thesis, Cardiff University, 2008. http://orca.cf.ac.uk/54918/.
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Causality plays a central role in human reasoning, in particular, in common human decision-making, by providing a basis for strategy selection. The main aim of the research reported in this thesis is to develop a new way to identify dynamic causal relationships between attributes of a system. The first part of the thesis introduces the development of a new data mining algorithm, called Dynamic Causal Mining (DCM), which extracts rules from data sets based on simultaneous time stamps. The rules derived can be combined into policies, which can simulate the future behaviour of systems. New rules can be added to the policies depending on the degree of accuracy. In addition, facilities to process categorical or numerical attributes directly and approaches to prune the rule set efficiently are implemented in the DCM algorithm. The second part of the thesis discusses how to improve the DCM algorithm in order to identify delay and feedback relationships. Fuzzy logic is applied to manage the rules and policies flexibly and accurately during the learning process and help the algorithm to find feasible solutions. The third part of the thesis describes the application of the suggested algorithm to a problem in the game-theoretic domain. This part concludes with the suggestion to use concept lattices as a method to represent and structure the discovered knowledge.
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Siderov, Mitkov Belin. "AUTONOMOUS MINING VEHICLE." Thesis, KTH, Industriell produktion, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-200894.
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Automation in mining industry is one of the important research and application areas of artificial intelligence. Also it is one of the key areas that autonomous vehicle technology being built upon. In order to accomplish autonomous driving, researchers get help from many different areas such as computer science, mechanical engineering, mathematics, and even psychology, and many more areas. With the current speed of technological development, in the near future, it will be inevitable that autonomous driving will be reality in many areas including mining areas, public and private transportation. It is obvious that autonomous vehicles will be major type of transportation when benefits of autonomous vehicles realized by the public. In this work, a lighting system for autonomous mining vehicle that has never been truly and intensively studied was developed. In this study, a state-of-the-art lighting system was designed and tested for realization of autonomous mining vehicle. Not only lighting system but also cleaning system for the surfaces of headlamps, sensors, and cameras has been developed and two patent application has been made. Also human vehicle interaction was studied.Automation i gruvindustrin är ett av de viktigaste forsknings- och tillämpningsområdena för artificiell intelligens. Det är också ett av nyckelområdena för autonom fordonsteknik. För att åstadkomma autonom körning, behöver forskare ta hjälp från många olika områden såsom t.ex. datavetenskap, maskinteknik, matematik men även psykologi. Med den nuvarande teknikutvecklingshastigheten så kommer det inom en snar framtid vara fullt möjligt för autonom körning att bli verklighet inom områden såsom t.ex. gruvnäringen samt offentliga och privata transporter. Det är uppenbart att förflyttning med autonoma fordon kommer vara en viktig typ av transport när fördelarna med autonoma fordon går upp för allmänheten. Detta arbete fokuserar på ett belysningssystem för ett autonomt gruvfordon, ett område som inte tidigare blivit särskilt ordentligt studerat. I denna studie har ett modernt belysningssystem utformats och testats för användande i autonoma gruvfordon. Studien täcker inte bara belysningssystemet utan även rengöringssystem för belysningsenheter, sensorer och kameror. Två patentansökningar har lämnats in. Även samspelet mellan människa och fordon har studerats.
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Zheng, George. "Web Service Mining." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/26324.
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In this dissertation, we present a novel approach for Web service mining. Web service mining is a new research discipline. It is different from conventional top down service composition approaches that are driven by specific search criteria. Web service mining starts with no such criteria and aims at the discovery of interesting and useful compositions of existing Web services. Web service mining requires the study of three main research topics: semantic description of Web services, efficient bottom up composition of composable services, and interestingness and usefulness evaluation of composed services. We first propose a Web service ontology to describe and organize the constructs of a Web service. We introduce the concept of Web service operation interface for the description of shared Web service capabilities and use Web service domains for grouping Web service capabilities based on these interfaces. We take clues from how Nature solves the problem of molecular composition and introduce the notion of Web service recognition to help devise efficient bottom up service composition strategies. We introduce several service recognition mechanisms that take advantage of the domain-based categorization of Web service capabilities and ontology-based description of operation semantics. We take clues from the drug discovery process and propose a Web service mining framework to group relevant mining activities into a progression of phases that would lead to the eventual discovery of useful compositions. Based on the composition strategies that are derived from recognition mechanisms, we propose a set of algorithms in the screening phase of the framework to automatically identify leads of service compositions. We propose objective interestingness and usefulness measures in the evaluation phase to narrow down the pool of composition leads for further exploration. To demonstrate the effectiveness of our framework and to address challenges faced by existing biological data representation methodologies, we have applied relevant techniques presented in this dissertation to the field of biological pathway discovery.Ph. D.
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Benkovská, Petra. "Web Usage Mining." Master's thesis, Vysoká škola ekonomická v Praze, 2007. http://www.nusl.cz/ntk/nusl-3950.
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General characteristic of web mining including methodology and procedures incorporated into this term. Relation to other areas (data mining, artificial intelligence, statistics, databases, internet technologies, management etc.) Web usage mining - data sources, data pre-processing, characterization of analytical methods and tools, interpretation of outputs (results), and possible areas of usage including examples. Suggestion of solution method, realization and a concrete example's outputs interpretation while using above mentioned methods of web usage mining.
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Payyappillil, Hemambika. "Data mining framework." Morgantown, W. Va. : [West Virginia University Libraries], 2005. https://etd.wvu.edu/etd/controller.jsp?moduleName=documentdata&jsp%5FetdId=3807.
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Thesis (M.S.)--West Virginia University, 2005Title from document title page. Document formatted into pages; contains vi, 65 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 64-65).
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Mina, Marco. "Mining Biological Networks." Doctoral thesis, Università degli studi di Padova, 2013. http://hdl.handle.net/11577/3422641.
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This thesis addresses relevant issues related to the analysis of biological networks. Path redundancy was exploited to denoise currently available data, dominated by high levels of wrong or missing information, and applied to the local alignment of protein-protein interaction networks. On another research direction, regulatory networks were employed to explain master regulators’ ability of modulating cells’ behaviour. In this direction, an existing approach was adapted for the analysis of miRNAs’ role in Glioblastoma Multiforme cancer cells. The methodological aspects of this work represent an improvement of the foundamental elements of network analysis techniques.In questa tesi sono stati affrontati alcuni aspetti problematici legati all’analisi di reti biologiche. Concentrandosi sull’allineamento di reti di interazione proteica, è stato studiato l’uso di metodi basati sul ”path redundancy“ per filtrare il rumore attualmente presente nei dati. In una seconda direzione di ricerca le reti di regolazione sono state sfruttate per spiegare la capacità dei ”master regulators“ di modulare il comportamento delle cellule, adattando di una pipeline d’analisi allo studio degli effetti dei miRNA nel Glioblastoma Multiforme. I progressi metodologici introdotti in questo lavoro contengono potenziali miglioramenti ad alcuni elementi comuni ad altre tecniche di analisi di reti.
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Delos, Reyes Julie Ann. "Mining shareholder value : financialisation, extraction and the geography of gold mining." Thesis, University of Manchester, 2017. https://www.research.manchester.ac.uk/portal/en/theses/mining-shareholder-value-financialisation-extraction-and-the-geography-of-gold-mining(d1f1b04a-1cd4-4577-b2ca-c44cc39f7583).html.
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This thesis examines the influence of institutional investors in the activities of large, publicly traded gold mining companies. As key sources of financing and dominant shareholders in company stocks, institutional investors have pushed for the maximisation of shareholder value as company goal. I examine the financial and operational realignments implemented by firms and their implications for production, growth and geography in the commodity boom and bust cycle of 2003-2015. I argue that the bid to deliver shareholder value manifested in highly fragmented, but interlinked, sites of accumulation: sharp swings in stocks and dividend payments that diverged from their actual basis in production, alongside increasing claims to future profitability through spatial restructuring. I theorise the process as contradictory-laden and crisis-prone as mineral extraction came to be mediated by the yield requirements, investment motives and risk tolerance of institutional investors. The thesis contributes to key debates on financialisation and mineral extraction within geography, political ecology and the financialisation literature.
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Lydiatt, Tracy, Patricia Mequita, and Anne Nolan. "Sustainable Mining? Applying the Framework for Strategic Sustainable Development to Mining Projects." Thesis, Blekinge Tekniska Högskola, Avdelningen för maskinteknik, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3922.
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Precious and base metal mining projects can serve as a stepping-stone in moving the mining industry towards achieving compliance with a scientific-principled definition of global socio-ecological sustainability. Using the Framework for Strategic Sustainable Development to assess the current reality of mine project development has resulted in identifying gaps between current best practices and a desired vision of sustainability constrained by science based principles. These gaps provide opportunities for sustainability driven innovation. Evaluation of mining project phases and their impacts on ecological and social systems using the four Sustainability Principles highlight specific opportunities to create value for social, economic and ecologic systems. Companies choosing to develop mining projects using the Framework for Strategic Sustainable Development can expect to achieve many business benefits, including improved reputation, increased transparency and stakeholder trust. Strengthening these aspects will provide robust support to companies as they manoeuvre to define their role in a sustainable society. This thesis examines how current processes for mining projects can be developed to support a successful transition into a sustainable society.
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Pietrzela, Mateusz. "Mining and Sustainability? Systems and Stakeholder Analyses of Uranium Mining in Namibia." Thesis, Uppsala universitet, Institutionen för geovetenskaper, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-204172.
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Roughly 10% of the Namibian GDP and over 40% of total exports are dependent on themining sector. Namibia is one of the five leading uranium producing countries worldwide withperspectives to triple the production in the following years. This study aims to identify the implicationsto sustainable development of the country carried by such a strategy to stimulate the economic growth.The complexity of the issue is addressed by an interdisciplinary set of methods leading to a betterunderstanding of processes linking uranium mining in Namibia with the environment, society and theglobal economy. Regulatory, trade and production systems are outlined and assessed, after which astakeholder analysis is conducted in order to determine who are the most influential actors as well asparties affected by the uranium production in Namibia. The results reveal a great dependence of the Namibian uranium mining sector on external factors, with the government perceived as the most affected stakeholder.
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Zhang, Nan. "Privacy-preserving data mining." [College Station, Tex. : Texas A&M University, 2006. http://hdl.handle.net/1969.1/ETD-TAMU-1080.
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Hulten, Geoffrey. "Mining massive data streams /." Thesis, Connect to this title online; UW restricted, 2005. http://hdl.handle.net/1773/6937.
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Büchel, Nina. "Faktorenvorselektion im Data Mining /." Berlin : Logos, 2009. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=019006997&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.
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Canturk, Deniz. "Time-based Workflow Mining." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/12606149/index.pdf.
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Contemporary workflow management systems are driven by explicit process models, i.e., a completely specified workflow design is required in order to enact a given workflow process. Creating a workflow design is a complicated time-consuming process and typically there are discrepancies between the actual workflow processes and the processes as perceived by the management. Therefore, new techniques for discovering workflow models have been required. Starting point for such techniques are so-called &ldquoworkflow logs"
containing information about the workflow process as it is actually being executed. In this thesis, new mining technique based on time information is proposed. It is assumed that events in workflow logs bear timestamps. This information is used in to determine task orders and control flows between tasks. With this new algorithm, basic workflow structures, sequential, parallel, alternative and iterative (i.e., loops) routing, and advance workflow structure or-join can be mined. While mining the workflow structures, this algorithm also handles the noise problem.
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Shao, Junming. "Synchronization Inspired Data Mining." Diss., lmu, 2011. http://nbn-resolving.de/urn:nbn:de:bvb:19-137356.
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Tigerström, Viktor. "Micropayments through cryptocurrency mining." Thesis, Uppsala universitet, Institutionen för informatik och media, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-303357.
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The monetary policies of states and systems built upon them do not naturally allow transactions of a very small value, as the transaction costs exceeds the actual value of the transaction. These types of transactions are called micropayments. This is problematic as it removes the possibility to monetize content that has a valuation that is so low that the costs of the transaction exceeds the value of the content. In this thesis we aim to create a system that allows micropayments to monetize low value content. We do so by developing a design theory based on Gregor and Jones conceptual model for design theories within Information Systems research. The system that we develop will use the end users computational power to generate a value, by running a cryptocurrency miner. We present the background knowledge required to fully understand the presented design theory. Within the design theory, we present a theoretical framework to base systems on that enables micropayments through cryptocurrency mining. We also present a developed proof of work prototype that proves the validity of the theoretical framework. Lastly we discuss our design theory. We conclude that the design theory enables transactions of a very low value, such as 0,0001 \$ cents. Transactions of such small value is not possible with systems built upon states monetary policies. We also conclude that the proposed design theory can be further developed to function independently of cryptocurrency mining. Instead the value for the transaction could be generated through solving complicated problems if institutions are willing to pay for computational power to solve them.
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Wang, Xiaohong. "Data mining with bilattices." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ59344.pdf.
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Jagannath, Sandhya. "Utility Guided Pattern Mining." NCSU, 2003. http://www.lib.ncsu.edu/theses/available/etd-11262003-131929/.
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This work is an initial exploration of the use of the decision-theoretic concept of utility to guide pattern mining. We present the use of utility functions as against thresholds and constraints as the mechanism to express user preferences and formulate several pattern mining problems that use utility functions. Utility guided pattern mining provides the twin benefits of capturing user preferences precisely using utility functions and of expressing user focus by choosing an appropriate utility guided pattern mining problem. It addresses the drawbacks of threshold guided pattern mining, the specification of threshold and the assumption of a fixed level of interest. We examine the problem of mining patterns with the best utility values in detail. We examine monotonicity properties of utility functions and the composition of utility functions from sub-utility functions as mechanisms to prune the search space. We also present a top-down approach for generating projected databases from FP-Trees, which is an order of magnitude faster than methods proposed in the literature.
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Lu, Zhiyong. "Text mining on GeneRIFs /." Connect to full text via ProQuest. Limited to UCD Anschutz Medical Campus, 2007.
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Thesis (Ph.D. in ) -- University of Colorado Denver, 2007.Typescript. Includes bibliographical references (leaves 174-182). Free to UCD affiliates. Online version available via ProQuest Digital Dissertations;
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Knobbe, Arno J. "Multi-relational data mining /." Amsterdam [u.a.] : IOS Press, 2007. http://www.loc.gov/catdir/toc/fy0709/2006931539.html.
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Lilliemarck, Jakob. "Super Local Urban Mining." Thesis, Konstfack, Industridesign, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:konstfack:diva-4185.
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Feng, Jing. "Information-theoretic graph mining." Diss., Ludwig-Maximilians-Universität München, 2015. http://nbn-resolving.de/urn:nbn:de:bvb:19-183384.
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Real world data from various application domains can be modeled as a graph, e.g. social networks and biomedical networks like protein interaction networks or co-activation networks of brain regions. A graph is a powerful concept to model arbitrary (structural) relationships among objects. In recent years, the prevalence of social networks has made graph mining an important center of attention in the data mining field. There are many important tasks in graph mining, such as graph clustering, outlier detection, and link prediction. Many algorithms have been proposed in the literature to solve these tasks. However, normally these issues are solved separately, although they are closely related. Detecting and exploiting the relationship among them is a new challenge in graph mining. Moreover, with data explosion, more information has already been integrated into graph structure. For example, bipartite graphs contain two types of node and graphs with node attributes offer additional non-structural information. Therefore, more challenges arise from the increasing graph complexity. This thesis aims to solve these challenges in order to gain new knowledge from graph data.
An important paradigm of data mining used in this thesis is the principle of Minimum Description Length (MDL). It follows the assumption: the more knowledge we have learned from the data, the better we are able to compress the data. The MDL principle balances the complexity of the selected model and the goodness of fit between model and data. Thus, it naturally avoids over-fitting.
This thesis proposes several algorithms based on the MDL principle to acquire knowledge from various types of graphs: Info-spot (Automatically Spotting Information-rich Nodes in Graphs) proposes a parameter-free and efficient algorithm for the fully automatic detection of interesting nodes which is a novel outlier notion in graph. Then in contrast to traditional graph mining approaches that focus on discovering dense subgraphs, a novel graph mining technique CXprime (Compression-based eXploiting Primitives) is proposed. It models the transitivity and the hubness of a graph using structure primitives (all possible three-node substructures). Under the coding scheme of CXprime, clusters with structural information can be discovered, dominating substructures of a graph can be distinguished, and a new link prediction score based on substructures is proposed. The next algorithm SCMiner (Summarization-Compression Miner) integrates tasks such as graph summarization, graph clustering, link prediction, and the discovery of the hidden structure of a bipartite graph on the basis of data compression. Finally, a method for non-redundant graph clustering called IROC (Information-theoretic non-Redundant Overlapping Clustering) is proposed to smartly combine structural information with non-structural information based on MDL. IROC is able to detect overlapping communities within subspaces of the attributes.
To sum up, algorithms to unify different learning tasks for various types of graphs are proposed. Additionally, these algorithms are based on the MDL principle, which facilitates the unification of different graph learning tasks, the integration of different graph types, and the automatic selection of input parameters that are otherwise difficult to estimate.
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丁嘉慧 and Ka-wai Ting. "Time sequences: data mining." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B31226760.
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Wan, Chang, and 萬暢. "Mining multi-faceted data." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hdl.handle.net/10722/197527.
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Multi-faceted data contains different types of objects and relationships between them. With rapid growth of web-based services, multi-faceted data are increasing (e.g. Flickr, Yago, IMDB), which offers us richer information to infer users’ preferences and provide them better services. In this study, we look at two types of multi-faceted data: social tagging system and heterogeneous information network and how to improve service such as resources retrieving and classification on them.
In social tagging systems, resources such as images and videos are annotated with descriptive words called tags. It has been shown that tag-based resource searching and retrieval is much more effective than content-based retrieval. With the advances in mobile technology, many resources are also geo-tagged with location information. We observe that a traditional tag (word) can carry different semantics at different locations. We study how location information can be used to help distinguish the different semantics of a resource’s tags and thus to improve retrieval accuracy. Given a search query, we propose a location-partitioning method that partitions all locations into regions such that the user query carries distinguishing semantics in each region. Based on the identified regions, we utilize location information in estimating the ranking scores of resources for the given query. These ranking scores are learned using the Bayesian Personalized Ranking (BPR) framework. Two algorithms, namely, LTD and LPITF, which apply Tucker Decomposition and Pairwise Interaction Tensor Factorization, respectively for modeling the ranking score tensor are proposed. Through experiments on real datasets, we show that LTD and LPITF outperform other tag-based resource retrieval methods.
A heterogeneous information network (HIN) is used to model objects of different types and their relationships. Meta-paths are sequences of object types. They are used to represent complex relationships between objects beyond what links in a homogeneous network capture. We study the problem of classifying objects in an HIN. We propose class-level meta-paths and study how they can be used to (1) build more accurate classifiers and (2) improve active learning in identifying objects for which training labels should be obtained. We show that class-level meta-paths and object classification exhibit interesting synergy. Our experimental results show that the use of class-level meta-paths results in very effective active learning and good classification performance in HINs.published_or_final_version
Computer Science
Master
Master of Philosophy
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Khodabandelou, Ghazaleh. "Mining Intentional Process Models." Phd thesis, Université Panthéon-Sorbonne - Paris I, 2014. http://tel.archives-ouvertes.fr/tel-01010756.
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Jusqu'à présent, les techniques de fouille de processus ont modélisé les processus en termes des séquences de tâches qui se produisent lors de l'exécution d'un processus. Cependant, les recherches en modélisation du processus et de guidance ont montrée que de nombreux problèmes, tels que le manque de flexibilité ou d'adaptation, sont résolus plus efficacement lorsque les intentions sont explicitement spécifiées. Cette thèse présente une nouvelle approche de fouille de processus, appelée Map Miner méthode (MMM). Cette méthode est conçue pour automatiser la construction d'un modèle de processus intentionnel à partir des traces d'activités des utilisateurs. MMM utilise les modèles de Markov cachés pour modéliser la relation entre les activités des utilisateurs et leurs stratégies (i.e., les différentes façons d'atteindre des intentions). La méthode comprend également deux algorithmes spécifiquement développés pour déterminer les intentions des utilisateurs et construire le modèle de processus intentionnel de la Carte. MMM peut construire le modèle de processus de la Carte avec différents niveaux de précision (pseudo-Carte et le modèle du processus de la carte) par rapport au formalisme du métamodèle de Map. L'ensemble de la méthode proposée a été appliqué et validé sur des ensembles de données pratiques, dans une expérience à grande échelle, sur les traces d'événements des développeurs de Eclipse UDC.
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GarciÌa-Osorio, CeÌsar. "Data mining and visualization." Thesis, University of Exeter, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.414266.
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Wang, Grant J. (Grant Jenhorn) 1979. "Algorithms for data mining." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/38315.
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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (p. 81-89).
Data of massive size are now available in a wide variety of fields and come with great promise. In theory, these massive data sets allow data mining and exploration on a scale previously unimaginable. However, in practice, it can be difficult to apply classic data mining techniques to such massive data sets due to their sheer size. In this thesis, we study three algorithmic problems in data mining with consideration to the analysis of massive data sets. Our work is both theoretical and experimental - we design algorithms and prove guarantees for their performance and also give experimental results on real data sets. The three problems we study are: 1) finding a matrix of low rank that approximates a given matrix, 2) clustering high-dimensional points into subsets whose points lie in the same subspace, and 3) clustering objects by pairwise similarities/distances.
by Grant J. Wang.
Ph.D.
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Anwar, Muhammad Naveed. "Data mining of audiology." Thesis, University of Sunderland, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.573120.
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This thesis describes the data mining of a large set of patient records from the hearing aid clinic at James Cook University Hospital in Middlesbrough, UK. As typical of medical data in general, these audiology records are heterogeneous, containing the following three different types of data: Audiograms (graphs of hearing ability at different frequencies) Structured tabular data (such as gender, date of birth and diagnosis) Unstructured text (specific observations made about each patient in a free- text or comment field) This audiology data set is unique, as it contains records of patients prescribed with both ITE and BTE hearing aids. ITE hearing aids are not generally available on the British National Health Service in England, as they are more expensive than BTE hearing aids. However, both types of aids are prescribed at James Cook University Hospital in Middlesbrough, UK, which is also an important feature of this data. There are two research questions for this research: Which factors influence the choice of ITE (in the ear) as opposed to BTE (behind the ear) hearing aids? For patients diagnosed with tinnitus (ringing in the ear), which factors influence the decision whether to fit a tinnitus masker (a gentle sound source, worn like a hearing aid, designed to drown out tinnitus)? A number of data mining techniques, such as clustering of audiograms, association analysis of variables (such as, age, gender, diagnosis, masker, mould and free text keywords) using contingency tables and principal component analysis on audiograms were used to find candidate variables to be combined into a decision support system (OSS) where unseen patient records are presented to the system, and the relative likelihood that a patient should be fitted with an ITE as opposed to a BTE aid or a tinnitus with masker as opposed to tinnitus not with masker is returned. The DSS was created using the techniques of logistic regression, Nalve Bayesian analysis and Bayesian network, and these systems were tested using 5 fold cross validations to see which of the techniques produced the better results. The advantage of these techniques for the combination of evidence is that it is easy to see which variables contributed to the final d~~Jpion. The constructed models and the data behind them were validated by"presenting them to the Principal audiologist, Dr. Robertshaw at James Cook University Hospital in Middlesbrough for comments and suggestions for improvements. The techniques developed in this thesis for the construction of prediction models were also used successfully on a different audiology data set from Malaysia. These decisions are typically made by audiology technicians working in the out- patient clinics, on the basis of audiogram results and in consultation with the patients. In many cases, the choice is clear cut, but at other times the technicians might benefit from a second opinion given by an automatic system with an explanation of how that second opinion was arrived at.
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Gonçalves, Lea Silvia Martins. "Categorização em Text Mining." Universidade de São Paulo, 2002. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-22062015-202748/.
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Os avanços tecnológicos e científicos ocorridos nas últimas décadas têm proporcionado o desenvolvimento de métodos cada vez mais eficientes para o armazenamento e processamento de dados. Através da análise e interpretação dos dados, é possível obter o conhecimento. Devido o conhecimento poder auxiliar a tomada de decisão, ele se tornou um elemento de fundamental importância para diversas organizações. Uma grande parte dos dados disponíveis hoje se encontra na forma textual, exemplo disso é o crescimento vertiginoso no que se refere à internet. Como os textos são dados não estruturados, é necessário realizar uma série de passos para transformá-los em dados estruturados para uma possível análise. O processo denominado de Text Mining é uma tecnologia emergente e visa analisar grandes coleções de documentos. Esta dissertação de mestrado aborda a utilização de diferentes técnicas e ferramentas para Text Mining. Em conjunto com o módulo de Pré-processamento de textos, projetado e implementado por Imamura (2001), essas técnicas e ferramentas podem ser utilizadas para textos em português. São explorados alguns algoritmos utilizados para extração de conhecimento de dados, \"como: Vizinho mais Próximo, Naive Bayes, Árvore de Decisão, Regras de Decisão, Tabelas de Decisão e Support Vector Machines. Para verificar o comportamento desses algoritmos para textos em português, foram realizados alguns experimentos.The technological and scientific progresses that happened in the last decades have been providing the development of methods that are more and more efficient for the storage and processing of data. It is possible to obtain knowledge through the analysis and interpretation of the data. Knowledge has become an element of fundamental importance for several organizations, due to its aiding in decision making. Most of the data available today are found in textual form, an example of this is the Internet vertiginous growth. As the texts are not structured data, it is necessary to accomplish a series of steps to transform them in structured data for a possible analysis. The process entitled Text Mining is an emergent technology and aims at analyzing great collections of documents. This masters dissertation approaches the use of different techniques and tools for Text Mining, which together with the Text pre-processing module projected and implemented by Imamura (2001), can be used for texts in Portuguese. Some algorithms, used for knowledge extraction of data, such as: Nearest Neighbor, Naive Bayes, Decision Tree, Decision Rule, Decision Table and Support Vector Machines, are explored. To verify the behavior of these algorithms for texts in Portuguese, some experiments were realized.
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Santos, José Carlos Almeida. "Mining protein structure data." Master's thesis, FCT - UNL, 2006. http://hdl.handle.net/10362/1130.
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The principal topic of this work is the application of data mining techniques, in particular of machine learning, to the discovery of knowledge in a protein database.
In the first chapter a general background is presented. Namely, in section 1.1 we overview the methodology of a Data Mining project and its main algorithms. In section 1.2 an introduction to the proteins and its supporting file formats is outlined. This chapter is concluded with section 1.3 which defines that main problem we pretend to address with this work: determine if an amino acid is exposed or buried in a protein, in a discrete way (i.e.: not continuous), for five exposition levels: 2%, 10%, 20%, 25% and 30%.
In the second chapter, following closely the CRISP-DM methodology, whole the process of construction the database that supported this work is presented. Namely, it is described the process of loading data from the Protein Data Bank, DSSP and SCOP. Then an initial data exploration is performed and a simple prediction model (baseline) of the relative solvent accessibility of an amino acid is introduced. It is also introduced the Data Mining Table Creator, a program developed to produce the data mining tables required for this problem.
In the third chapter the results obtained are analyzed with statistical significance tests. Initially the several used classifiers (Neural Networks, C5.0, CART and Chaid) are compared and it is concluded that C5.0 is the most suitable for the problem at stake. It is also compared the influence of parameters like the amino acid information level, the amino acid window size and the SCOP class type in the accuracy of the predictive models.
The fourth chapter starts with a brief revision of the literature about amino acid relative solvent accessibility. Then, we overview the main results achieved and finally discuss about possible future work.
The fifth and last chapter consists of appendices. Appendix A has the schema of the database that supported this thesis. Appendix B has a set of tables with additional information. Appendix C describes the software provided in the DVD accompanying this thesis that allows the reconstruction of the present work.
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Friesen, Eugen. "ArcelorMittal: metals & mining." Master's thesis, NSBE - UNL, 2013. http://hdl.handle.net/10362/9876.
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Garda-Osorio, Cesar. "Data mining and visualisation." Thesis, University of the West of Scotland, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.742763.
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Rawles, Simon Alan. "Object-oriented data mining." Thesis, University of Bristol, 2007. http://hdl.handle.net/1983/c13bda2c-75c9-4bfa-b86b-04ac06ba0278.
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Attempts to overcome limitations in the attribute-value representation for machine learning has led to much interest in learning from structured data, concentrated in the research areas of inductive logic programming (ILP) and multi-relational data mining (MDRM). The expressivenessa nd encapsulationo f the object-oriented data model has led to its widespread adoption in software and database design. The considerable congruence between this model and individual-centred models in inductive logic programming presents new opportunities for mining object data specific to its domain. This thesis investigates the use of object-orientation in knowledge representation for multi-relational data mining. We propose a language for expressing object model metaknowledge and use it to extend the reasoning mechanisms of an object-oriented logic. A refinement operator is then defined and used for feature search in a object-oriented propositionalisation-based ILP classifier. An algorithm is proposed for reducing the large number of redundant features typical in propositionalisation. A data mining system based on the refinement operator is implemented and demonstrated on a real-world computational linguistics task and compared with a conventional ILP system. Keywords: Object orientation; data mining; inductive logic programming; propositionalisation; refinement operators; feature reduction
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Sandström, Anders. "Mining in Zero Gravity." Thesis, Umeå universitet, Designhögskolan vid Umeå universitet, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-150623.
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Regardless of new mining technologies and environmental regulations, the minerals we extract from the earth’s crust will eventually run out. Likewise, our society demands a constant increase of technology to improve our quality of life. Mining in Zero Gravity is a speculative design project that offers a vision of our first attempt at mining platinum group metals from asteroids by the year 2040. Kolibri is designed within the boundaries of the future challenges facing the mining industry and the development of our space industry.
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Njeru, Tom Magara. "Persistent reservations in mining?" Master's thesis, University of Cape Town, 2014. http://hdl.handle.net/11427/8511.
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Includes bibliographical references.This paper analyses the persistence of colour bar reservations into the present day mining sector. Focusing on the occupations Banksman/Onsetter, Blaster, Engineer, Labourer and Winding Engine Driver, an ordered probit regression is run producing little evidence to support the persistence. A White skill bias is noted and further investigated using Oaxaca decomposition. Observable skill sets such as education, experience, demographics and firm level characteristics are unable to adequately explain the occupational gap between the races. This might suggests some skill based discrimination is still rife, however with various unobservable characteristics the model cannot control for; a causal relationship cannot be confidently concluded.
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Mao, Shihong. "Comparative Microarray Data Mining." Wright State University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=wright1198695415.
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Novák, Petr. "Data mining časových řad." Master's thesis, Vysoká škola ekonomická v Praze, 2009. http://www.nusl.cz/ntk/nusl-72068.
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