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 65 for “"domain specific knowledge"”.
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Mapping relational databases to semantic web using domain-specific knowledge
… suitable structural definitions ("data schema"), specific instances of them ("data") and their use ("access rights"), but also semantically using a logical model which allows formal interpretation and sound logical inferencing about the information ("knowledge"). Relational models are limited to …
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Injection of Domain-Specific Knowledge for Enterprise Text-to-SQL
… to work with enterprise data as well as using knowledge-injection to enhance the performance of LLMs on Text-to-SQL tasks. We begin by evaluating the baseline performance of LLMs on enterprise databases, revealing that a predominant source of failure stems from a lack of domain-specific …
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The Creative Process: The Effects of Domain Specific Knowledge and Creative Thinking Techniques on Creativity
… on creativity is unclear. These two factors are domain-specific knowledge and creative thinking techniques. The first of these factors relates to the first stage of the creative thinking process (problem definition), specifically the extent to which informational cues prime domain specific …
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Reflexive Composition: Bidirectional Enhancement of Language Models and Knowledge Graphs
… factual inconsistencies, and restricted domain-specific knowledge. Knowledge Graphs (KGs), by contrast, provide structured and verifiable information but are expensive to build and maintain manually. This thesis introduces Reflexive Composition, a bidirectional integration framework in …
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Modeling information processing components and structural knowledge representations in pilot judgment
… using information processing components and knowledge representations in long term memory (LTM) as individual difference measures to predict performance. The objective was to determine which of these two classes of measures predicted pilot judgment performance for groups of varying levels of …
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Dynamic graph neural network framework for real-time multi-modal data analysis and predictive modeling
… interactions among temporal, spatial, and domain-specific knowledge, particularly as these factors evolve dynamically, while also accounting for the complexities of multi-modal data in real time, with current GNN architectures often falling short in leveraging cross-modal correlations. We …
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CADIA-Player : a general game playing agent
… be able to learn a strategy without having any domain-specific knowledge provided by their developers. The most successful GGP agents have so far been based on the traditional approach of using game-tree search augmented with an automatically learned evaluation function for encapsulating the …
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Implementing Robust and Efficient Pseudo-transient Methods for Solving Neural Complementarity Problems in Julia
… systems, there is a pressing need to integrate domain-specific knowledge into the modeling process, a task for which explicit neural networks may not be ideally suited. Recent studies, such as [2] and [4] have highlighted the potential of implicit layers in capturing more complex relationships …
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Children's Construction of Musical Knowledge in Early School
… musical learning and development proved to be domain-specific rather than domain-general. The construction of musical knowledge depended on accessibility of and familiarity with the specific musical repertoire rather than general physical or cognitive constraints. The children's domain specific …
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Mélange: Multi-tenant scheduling with adaptive eviction for graph processing clusters
… starvation. We propose novel ways of exploiting domain-specific knowledge to achieve better scheduling decisions for graph processing jobs. We evaluate static eviction policies and design Mélange to adapt to the cluster and job state at run time to reduce overhead costs during eviction. We have …
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Learning Generative Models Using Structured Latent Variables
… It is widely believed that learned prior knowledge must be utilized in order to tackle this problem. My dissertation tries to address some of these concerns by introducing domain-specific knowledge to standard deep learning models. This domain-specific knowledge is used to specify …
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Ormolu : generating runtime monitors from alloy models
… in regards to its type system. Ormolu allows domain specific knowledge to be expressed in Alloy, where it can be checked and verified. The same model can then be used to check if the constraints of the model are still satisfied at runtime. The feasibility of Ormolu is examined in the domain of …
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Enhancing General Language Models for Biomedical Test Retrieval via Diversified Prior Knowledge
The thesis introduces the Diversified Prior Knowledge Enhanced General Language Model (DPK-GLM) to improve the efficacy of general language models in biomedical Information Retrieval (IR). General language models often struggle with biomedical data due to its specialized terminology and the need …
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Knowledge Graphs and Large Language Models for Intelligent Applications in the Tourism Domain
… pivotal technologies underpinning this shift are Knowledge Graphs (KGs) and Data Lakes. Concurrently, Artificial Intelligence has emerged as a potent means to leverage data, creating knowledge and pioneering new tools across various sectors. Among these advancements, Large Language Models (LLM) …
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Self-Training for Natural Language Processing
… with public corpora to tasks that require domain-specific knowledge, different inference skills, unseen text styles, and explainability. In this thesis, we explore self-training methods for mitigating the data distribution gaps between training and evaluation domains and tasks. In contrast …
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Building Modular, Human-Interpretable AI Systems with Behavior Trees
… how manually designed behavior trees with domain-specific knowledge are capable to solve problems that were usually handled by human experts before. 2) Behavior tree for efficient hierarchical reinforcement learning. Behavior tree provides a modular problem formulation that facilitates …
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Triton: a domain specific language for cyber-physical systems
… resources, which requires extensive domain-specific knowledge. This work proposes Triton, a language focused on increasing abstraction by providing high-level domain-specific features to cyber-physical systems. We propose dedicated code blocks to handle task scheduling, constraint …
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i-Seek : an intelligent system for eliciting and explaining knowledge
… Intelligent System for Eliciting and Explaining Knowledge that leverages the OpenMind [1] Commonsense knowledge base in conjunction with domain- specific knowledge in Personal Finance, Technical Help, and Health domains to act as an advisory system for novice users. Most of the interfaces are …
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Detecting cells and analyzing their behaviors in microscopy images using deep neural networks
… such as radiologists and physicians. More specifically, these computer-aided methods are to help identify, classify and quantify patterns in medical images. Recent advances in machine learning, more specifically, in the way of deep learning, have made a big leap to boost the performance of …
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