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 59 for “"knowledge extraction"”.
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SKEWER: Sentiment Knowledge Extraction with Entity Recognition
… SKEWER, a pipeline for building a spoken-word knowledge graph from those transcripts. SKEWER utilizes a number of natural language processing tools to extract named entities, phrases, and sentiments from the transcript texts and aggregates the results of those tools into a graph database. The …
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A Turing Game for commonsense knowledge extraction
… of the field. Traditionally, commonsense knowledge is gathered by using humans to create and insert it in knowledge bases. Automating the collection of commonsense from text that is freely available can reduce the cost and effort of creating large knowledge bases and can enable systems …
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Scientific knowledge extraction from massive text data
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-04-12 without embargo terms
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ADAPTIVE FRAMEWORKS FOR KNOWLEDGE EXTRACTION IN HETEROGENEOUS DATA ENVIRONMENTS
… presents a significant challenge for effective knowledge extraction, due to the heterogeneous nature and the complexity of extracting meaningful patterns in environments presenting diverse data types. This thesis proposes SHIFT, the first seed-guided hierarchical topic modelling framework …
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Active Expert Sourcing; Knowledge Extraction from Domain Specific Information
The development of Named Entity Recognition (NER) in recent years is partially attributed to the availability of annotated ata-sets. Data-sets play a crucial part indeveloping, training, and testing NER algorithms. The need for data-sets becomes more important when adapting the algorithms to new …
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Techniques for automatic test knowledge extraction from compiled circuits
… has shown that the use of high-level test knowledge can be used to greatly accelerate the test generation process. The problem was that no techniques were developed to extract this knowledge from a circuit. Typically, the only solution for a circuit designer was to manually extract the test …
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Knowledge extraction from unstructured data and classification through distributed ontologies
… consists of a logic to distribute and mine the knowledge and of a set of physical peer nodes organized in a ring topology based on a Distributed Hash Table (DHT). Each node shares the same logic and provides an entry point that enables clients to query the knowledge base using atomic, …
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Natural Language Processing Solutions for Knowledge Extraction: NetME and EmotWion
… in two different domains, biomedical knowledge networks building and analysis of the contagion of emotions in social networks. In biomedical domain, with the increasing volume and unstructured nature of scientific literature most of the information embedded within them are lost. The …
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Effective knowledge extraction and knowledge-enhanced machine learning for health
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms
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Representation decomposition for knowledge extraction and sharing using restricted Boltzmann machines
… algorithms based on RBMs, the question of how knowledge is represented, and could be shared by such networks, has received comparatively little attention. Neural networks are notorious for being difficult to interpret. The area of knowledge extraction addresses this problem by translating …
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Organizational knowledge extraction from business process models = Szervezeti tudás kinyerése üzleti folyamatmodellekből
… research area is dedicated to the challenges of knowledge extraction from business processes. I analyzed the opportunities of knowledge extraction based on the literature, my research background and practical experiences. I am proposing a solution to extract, organize and preserve knowledge …
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Biologically Inspired Optimisation Algorithms for Transparent Knowledge Extraction Allied to Engineering Materials Processing
… hence the reason why it is often referred to as knowledge-driven modelling. On the contrary, knowledge extraction from data (or datadriven modelling), inspired principally from artificial intelligence techniques, is based on limited knowledge of the modelling process and relies on the data …
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Optimization, control, and knowledge extraction in engineering systems: Applications in vehicle suspension, thermal management, and floating offshore wind turbines
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2026-08-01
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Engineering System Design for Automated Space Weather Forecast. Designing Automatic Software Systems for the Large-Scale Analysis of Solar Data, Knowledge Extraction and the Prediction of Solar Activities Using Machine Learning Techniques
Coronal Mass Ejections (CMEs) and solar flares are energetic events taking place at the Sun that can affect the space weather or the near-Earth environment by the release of vast quantities of electromagnetic radiation and charged particles. Solar active regions are the areas where most flares and …
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Engineering System Design for Automated Space Weather Forecast. Designing Automatic Software Systems for the Large-Scale Analysis of Solar Data, Knowledge Extraction and the Prediction of Solar Activities Using Machine Learning Techniques.
Coronal Mass Ejections (CMEs) and solar flares are energetic events taking place at the Sun that can affect the space weather or the near-Earth environment by the release of vast quantities of electromagnetic radiation and charged particles. Solar active regions are the areas where most flares and …
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Knowledge Graph Extension by Entity Type Recognition
Knowledge graphs have emerged as a sophisticated advancement and refinement of semantic networks, and their deployment is one of the critical methodologies in contemporary artificial intelligence. The construction of knowledge graphs is a multifaceted process involving various techniques, where …
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Document Layout Analysis and Recognition Systems
<p>Automatic extraction of relevant knowledge to domain-specific questions from Optical Character Recognition (OCR) documents is critical for developing intelligent systems, such as document search engines, sentiment analysis, and information retrieval, since hands-on knowledge extraction by a …
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Computer-aided space planning for residential layouts: case-based learning and designer-computer interaction
… such research was limited by tractability and knowledge extraction issues, and a lack of research into how designers use automated design tools in practice. To address the tractability and knowledge extraction issues, a general data-driven direction was adopted for this research. In this …
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The Derivation of Ontological Structures From Folksonomies
… the framework, called Folksonomy Space, support knowledge extraction from a folksonomy are also introduced. The dimensions of Folksonomy Space are explored for amazon.com that will help to delineate salient features of tag sets, tags, taggers, and referenced objects. An analytic framework is …
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