Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 148 for “"Knowledge Discovery"”.
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Knowledge Discovery in Intelligence Analysis
… such large datasets from raw feeds to actionable knowledge but successful use of such methods require integrated frameworks for contextualizing them within the work processes of the analyst. Intelligence analysts typically distinguish between three classes of problems: collections, analysis, and …
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Knowledge Discovery for Sustainable Urban Mobility
Due to the rapid growth of urban areas, sustainable urbanization is an inevitable task for city planners to address major challenges in resource management across different sectors. Sustainable approaches of energy production, distribution, and consumption must take the place of traditional methods …
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Concept Based Knowledge Discovery from Biomedical Literature
… describes and introduces novel methods for knowledge discovery and presents a software system that is able to extract information from biomedical literature, review interesting connections between various biomedical concepts and in so doing, generates new hypotheses. The experimental results …
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Knowledge discovery and modeling in genomic databases
… that GeneScout is comparable to existing gene discovery tools and complements the widely used GenScan system.
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A geographic knowledge discovery approach to property valuation
This thesis involves an investigation of how knowledge discovery can be applied in the area Geographic Information Science. In particular, its application in the area of property valuation in order to reveal how different spatial entities and their interactions affect the price of the properties is …
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Knowledge discovery for stochastic models of biological systems
… methods and approaches to tackle the problem of knowledge discovery in computational biology from a stochastic perspective. Major bottlenecks in adopting a stochastic representation can be overcome with the use of proper methodologies by integrating statistics and computer science. In particular …
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Exploiting language models for annotation-efficient knowledge discovery
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-03-01 without embargo terms
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Feature extraction and knowledge discovery in process operation analysis
… methods; and (3) automatic extraction of knowledge rules from process operational data and embedding of the extracted knowledge in the structure and weights of fuzzy-neural networks. The methodologies and the prototype system which have been developed are illustrated and evaluated using …
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Analyzing information flow in social networks for knowledge discovery
… rich opportunities for the development of knowledge discovery algorithms which will find immense value in revealing trends, latent structures or interesting behaviors in these social systems. In any social system, communication exposes people to information, opinions as well as behavior of …
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Knowledge discovery in biological databases : a neural network approach
Knowledge discovery, in databases, also known as data mining, is aimed to find significant information from a set of data. The knowledge to be mined from the dataset may refer to patterns, association rules, classification and clustering rules, and so forth. In this dissertation, we present a …
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Knowledge Discovery from Complex Event Time Data with Covariates
<p>In particular engineering applications, such as reliability engineering, complex types of data are encountered which require novel methods of statistical analysis. Handling covariates properly while managing the missing values is a challenging task. These type of issues happen frequently in …
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Knowledge Discovery and Machine Learning in Construction Project Databases
… to convert construction project data into knowledge. This paper shows the nine steps in the KDD process: (i) understanding and defining the problem, (ii) collecting data, (iii) exploring data, (iv) cleaning data, (v) enhancing data, (vi) selecting data attributes, (vii) mining data, (viii) …
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Probabilistic latent variable models for knowledge discovery and optimization
… variable models (PLVMs) with applications to knowledge discovery and optimization. Probabilistic modeling is a principled means to gain insight of data. By assuming that the observed data are generated from a distribution, we can estimate its density, or the statistics of our interest, by …
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Decreasing Occlusion and Increasing Explanation in Interactive Visual Knowledge Discovery
… are the major problems for interactive visual knowledge discovery, machine learning and data mining in multidimensional data. This thesis proposes a hybrid method that combines visual and analytical means to deal with these problems. This method, denoted as FSP, uses visualization of n-D data …
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Accelerating scientific research: Empowering automated knowledge discovery through machine learning
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2025-12-01
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Knowledge discovery in corporate email : the compliance bot meets Enron
… become research fodder for those interested in "Knowledge Discovery," a computer science discipline that gleans meaningful information from data otherwise indecipherable due to its sheer size. CEO's and other C-level corporate managers are my intended audience, so I have attempted to counter the …
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Automatic Question Answering and Knowledge Discovery from Electronic Health Records
… we propose to achieve this goal by querying a knowledge base constructed based on fine-grained document-level expert annotations of clinical records for various NLP tasks. We first create a dataset for clinical knowledge base question answering with two sets: clinical knowledge base and …
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Effective semantic-based keyword search over relational databases for knowledge discovery
… without having to know any SQL or having any knowledge of the underlying structure of the data. In this research work our primary focus is to enhance the effectiveness of the keyword search over relational databases using semantic web technologies. We have also addressed some the issues with …
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Computational knowledge discovery techniques and their application to options market databases
… has evolved, collectively termed 'computational knowledge discovery techniques' in this work. Preliminary evidence suggests that certain of these techniques are superior to parametric approaches in pricing options. Statistical confidence in models is of paramount importance in finance, hence …
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