737 search results for “data mining” in the Public website
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Data Mining and Sports
Collecting data in sports increased in importance the last few years.
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Applying data mining in telecommunications
This thesis applies data mining in commercial settings in the telecommunications industry.
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Exploratory Data Mining in Multimodal data
The change from a closed institution to an open living environment for patients with late stages of dementia will give the patients more freedom in their day-to-day life. The effect of this change on the patients’ mobility, activity and interaction with others will be assessed with sensor technology…
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Data mining and algorithm development
Due to the modern techniques of combinatorial chemistry and high-throughput screening, data on the biological activity of many millions of compounds is known. However, it is still very difficult to transfer this data into knowledge: if we know that compounds A and B bind to a certain protein with high…
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DAMIOSO - data mining on high volume simulation output
Modern computer-aided simulation tools used by various industries produce gigabytes of data. But currently, they take days and even up to weeks of computation effort. To make the best use of all these data, the DAMIOSO project focuses on developing algorithms and tools for managing, mining, and optimizing…
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Structural Health Monitoring Meets Data Mining
Promotor: Prof.dr. J.N. Kok, Co-promotor: Dr. A.J. Knobbe
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Multi-dimensional feature and data mining
In this thesis we explore machine and deep learning approaches that address keychallenges in high dimensional problem areas and also in improving accuracy in wellknown problems. In high dimensional contexts, we have focused on computational fluid dynamics (CFD) simulations.
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Knowledge Discovery and Data Mining from patient experience repositories
This project develops a scientific method to extract clinically relevant new information from patient forum websites that discuss patient experiences concerning e.g. medication, nutrition, co-morbidities, genetic factors etc.
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Mining Sensor Data from Complex Systems
Promotor: J.N. Kok, Co-Promotor: A.J. Knobbe
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Discrimination and Privacy in the Information Society; Data Mining and Profiling in Large Databases
Latest technological developments in data mining and profiling.
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The Power of Knowledge Ethical, Legal and Technological Aspects of Data Mining and Group Profiling in Epidemiology
With the rise of information and communication technologies, large amounts of data are being generated and stored in databases. In order to get a better grip on these large amounts of data, serious efforts are being made to discover patterns and relations in the data with the help of new techniques.…
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SAPPAO - Optimizing the flight times of airplanes using data science
The SAPPAO project aims to optimise the accuracy and reliability of predicting scheduled flight times. The full name of the project is 'A Systems Approach towards Data Mining and Prediction in Airlines Operations'.
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Algorithms for analyzing and mining real-world graphs
Promotor: Prof.dr. J.N. Kok, Co-Promotor: W.A. Kosters
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Algorithmic tools for data-oriented law enforcement
Promotor: J.N. Kok, Co-promotor: W.A. Kosters
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Bastienne Vriesendorp
Science
b.vriesendorp@biology.leidenuniv.nl | +31 71 527 2727
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Data-Driven Drug Discovery Network (D4N)
The Data-Driven Drug Discovery Network (D4N) is an initiative by researchers from Leiden University and collaborators to join efforts in applying and developing novel techniques from data science to drug discovery and related topics from bioinformatics.
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Urban Mine of the Netherlands
What is the size and composition of the Dutch urban mine? How will the urban mine develop over time, and how can it be used as a source of materials as part of a circular economy?
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Pattern mining for label ranking
Promotor: J.N. Kok, Co-promotor: C.M. Soares, A.J. Knobbe
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Mining conflicts
An effective and equitable approach to resource conflicts?
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Data science
The majority of scientists, from archaeologists through to zoologists, collect enormous volumes of data. Their massive databases contain large amounts of information which is difficult for humans to filter. With a solid grounding in statistics and computer science, we can develop algorithms for analyzing…
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Explainatory Data Analysis
The Explainatory Data Analysis group develops algorithms and theory that enable domain experts to explain data by finding interpretable patterns and models.
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Data Science
The majority of scientists, from archaeologists through to zoologists, collect huge volumes of data. Their massive databases contain large amounts of information which is difficult for humans to filter. With a solid grounding in statistics, we can develop algorithms for analysing and identifying patterns…
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Nees Jan van Eck
Faculteit der Sociale Wetenschappen
ecknjpvan@cwts.leidenuniv.nl | +31 71 527 6445
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Data Driven Modeling & Optimization of Industrial Processes
Industrial manufacturing processes, such as the production of steel or the stamping of car body parts, are complex semi-batch processes with many process steps, machine parameters and quality indicators.
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Data Science: Computer Science (MSc)
The master's specialisation Data Science: Computer Science at Leiden University provides students thorough knowledge and understanding of statistical and computational aspects of data analysis, including their application in databases, advances in data mining, networks, pattern recognition, and deep…
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Mining the mentor's mind
The elicitation of mentor teachers' practical knowledge by prospective teachers
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PUMA (Prospecting the Urban Mines of Amsterdam)
PUMA aims at composing a geological map of the urban mine of Amsterdam for a selection of metals. Where are main deposits of copper, iron and aluminium located, when will they become available for secondary production, in what state and shape are they?
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Text Mining and Retrieval Leiden (TMRL)
Text Mining and Retrieval Leiden (TMRL) focusses on text mining and retrieval problems in complex domains.
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Frank Takes
Science
f.w.takes@liacs.leidenuniv.nl | +31 71 527 7143
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Mining and environmental protection in Indonesia
On 24 April, Feby Kartikasari defended the thesis 'Mining and environmental protection in Indonesia: regulatory pitfalls'. The doctoral research was supervised by Adriaan Bedner and Bernardo Ribeiro de Almeida.
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Robust rules for prediction and description.
In this work, we attempt to answer the question:
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Matthijs van Leeuwen
Science
m.van.leeuwen@liacs.leidenuniv.nl | +31 71 527 7048
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Methods and Tools for Mining Multivariate Time Series
Mining time series is a machine learning subfield that focuses on a particular data structure, where variables are measured over (short or long) periods of time.
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Using data to improve sports performances
‘Tell me something I don’t know,’ said skating coach Jac Orie to Leiden data scientist Arno Knobbe. And he did. Knobbe and his colleagues now assist athletes in all kinds of ways with the help of data mining.
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Astronomy and Data Science (MSc)
The Astronomy and Data Science master’s specialisation at Leiden University combines advanced Astronomy courses with relevant courses from the Computer Science programme at Leiden University.
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International Environmental Obligations and Liabilities in Deep Seabed Mining
On dinsdag 26 juni 2018, Linlin Sun defended her doctoral thesis ‘International Environmental Obligations and Liabilities in Deep Seabed Mining’. The doctoral research was supervised by Prof. dr. N.J. Schrijver en Prof. dr. E.C.P.D.C. De Brabandere.
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Niki van Stein
Science
n.van.stein@liacs.leidenuniv.nl | +31 71 527 2727
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Massively collaborative machine learning
Promotor: J. N. Kok, Co-promotor: A. J. Knobbe
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Labour in the Establishment of the Iranian Copper Mining Industry: The Sarechhemseh Copper Mine 1966-1979
Abdolreza Alamdar Baghini defended his thesis on 5 December 2019.
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Data Science
The ability to collect and interpret huge quantities of data has become indispensable to society and academia. Leiden University is a knowledge and expertise centre for data science that places the emphasis on interdisciplinary collaboration and innovation.
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CEEDs, the Collective Experience of Empathic Data Systems
The Collective Experience of Empathic Data Systems (CEEDs) consortium developed novel integrated technologies that support experiencing, analysing and understanding of very large datasets.
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What's mine is yours and what's yours is mine: Teacher communities as a means to increase adoption of Open Educational Resources in curricula
Open Educational Resources (OER) have the potential to change teaching in Higher Education, but adoption is low despite the growing amount of resources available. The current project aims to investigate if and how teacher communities can foster adoption of OER in curricula.
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EU Erasmus+ Curriculum Development in Data Science and Artificial Intelligence
LIACS is a partner in the EU Erasmus+ Curriculum Development for the Asian education system. The knowledge available in the field of Data Science and Artificial Intelligence education will be shared and adapted for the Asian market.
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Bart Custers
Faculteit Rechtsgeleerdheid
b.h.m.custers@law.leidenuniv.nl | +31 71 527 8838
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Data science for tax administration
In this PhD-thesis several new and existing data science application are described that are particularly focused on applications for tax administrations.
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‘For good measure’: data gaps in a big data world
Sarah Giest and Annemarie Samuels, both Assistant Professors at Leiden University, researched the quality and coverage of the data being collected for policiymakers to be used, specifically pertaining to minority groups.
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beyond conflict minerals: The complex links between artisanal gold mining and violence
Policy Note Insecurity in Burkina Faso – beyond conflict minerals: The complex links between artisanal gold mining and violence
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Digging in documents: using text mining to access the hidden knowledge in Dutch archaeological excavation reports
The archaeology domain produces large amounts of texts, too much to effectively read or manually search through for research. To alleviate this problem, we created a search system (called AGNES), which combines full text search with entity and geographical search.
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Robust Estimation using Aggregated Data for Urban policy making (READ-URBAN)
Read-Urban was a first project to investigate whether policy recommendations can be made with the aid of linked data collections and data science and to gain experience with the success factors for such a process.
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Mining the kinematics of discs to hunt for planets in formation
Detecting planets during their formation stages is crucial for understanding the history and diversity of fully developed planetary systems like our own. However, observing young planets directly is challenging because they are often deeply embedded within their host protoplanetary discs, rich in gas…