397 search results for “text mining” in the Public website
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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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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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Knowledge discovery from patient forums: gaining novel medical insights from patient experiences
Patients share valuable advice and experiences with their peers in online patient discussion groups.
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Mining Sensor Data from Complex Systems
Promotor: J.N. Kok, Co-Promotor: A.J. Knobbe
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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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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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Data Mining and Sports
Collecting data in sports increased in importance the last few years.
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Nees Jan van Eck
Faculteit der Sociale Wetenschappen
ecknjpvan@cwts.leidenuniv.nl | +31 71 527 6445
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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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Applying data mining in telecommunications
This thesis applies data mining in commercial settings in the telecommunications industry.
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Mining the mentor's mind
The elicitation of mentor teachers' practical knowledge by prospective teachers
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Alex Brandsen
Faculteit Archeologie
a.brandsen@arch.leidenuniv.nl | +31 71 527 2727
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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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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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Algorithms for analyzing and mining real-world graphs
Promotor: Prof.dr. J.N. Kok, Co-Promotor: W.A. Kosters
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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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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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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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Karsten Lambers
Faculteit Archeologie
k.lambers@arch.leidenuniv.nl | +31 71 527 6510
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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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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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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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EXALT: Excavating Archaeological Literature
We will use Artificial Intelligence to make an intelligent, multilingual search engine for archaeological texts, which will enable new discoveries about the human past.
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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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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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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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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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Laboratories for Digital Archaeology
The Digital Archaeology research group manages two computer laboratories with different purposes: the teaching lab (F1.01) and the research lab (A1.13a).
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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…
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Gerrit van Uitert
Faculty of Humanities
g.c.van.uitert@hum.leidenuniv.nl | +31 71 527 2117
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Text-mining real-world data to evaluate systemic anti-cancer therapy
PhD defence
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A document classifier for medicinal chemistry publications trained on the ChEMBL corpus
Source: J Cheminform, Volume 6, Issue 1 (2014)
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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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Making everything we know computer-readable
Data and information should be stored in a way that computers can understand, says Barend Mons, professor of Biosemantics at the Leiden University Medical Center and Chair of the High Level Expert Group for the European Open Science Cloud. We speak with him about FAIR data, knowlets and nanopublicat…
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About this minor
Learn more about the minor Digital Humanities and Artificial Intelligence.
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DH Pilot Projects Symposium and Digital Skills Workshops – Winter Weeks
We hold the annual Digital Humanities Pilot Project Symposium and Digital Skills Winter Workshop Week in the last week of January. It is open to all LU staff and PhD/MA students.
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Golsa Nayeb Ghanbar Hosseini
Science
g.nayeb.ghanbar.hosseini@biology.leidenuniv.nl | +31 71 527 2727
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Was macht Hypertext mit Text? Textlinguistische Einsichten in das be- und entgrenzende Wirken von Paratext und Text in Hypertext
This dissertation focuses on the question how text and paratext contribute to the way that text in a network-like environment is clearly bordered and at the same time can easily be linked to other texts.
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Marja Oudega
Faculteit der Sociale Wetenschappen
m.h.oudega@fsw.leidenuniv.nl | +31 71 527 2727
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Special Interest Groups
Several so-called Special Interest Groups are linked to DSRP. These groups focus on specialized topics and organize their own group meetings, talks etc. Contact the group leader if you are interested to join. It is possible to be a member of multiple groups.
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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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Algorithmic tools for data-oriented law enforcement
Promotor: J.N. Kok, Co-promotor: W.A. Kosters
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textnets: A Python package for text analysis with networks
With textnets it is possible to visualize and analyze textual data in novel ways.
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Text in Context
Recontextualising the Papyri from Roman Soknopaiou Nesos / Dimê (Fayyum, Egypt)
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Computational linguistics
Computational linguistics uses computational methods to help answer linguistics questions across a variety of topics.
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Computational Linguistics
In this theme you will be supplied with a firm background in the core of current computational linguistics and a solid comprehension of its neighboring fields.
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A treasure trove of legal data
Data science offers great opportunities for legal research, according to Simone van der Hof and Bart Custers (eLaw). But at the same time, we have to keep an eye on the unwanted side effects of big data - such as ethnic profiling.
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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'.