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Showing 1 to 10 of 10 for “"Concept extraction"”.
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Syntax-based Concept Extraction For Question Answering
… representation, question analysis, and answer extraction may be evaluated in real world information extraction contexts. The task is to go beyond the representation of text documents as "bags of words" or data blobs that can be scanned for keyword combinations and word collocations in the …
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Concept extraction for disability insurance payment evaluation
… not replace, human evaluators. We automate the extraction of relevant parts of medical history files; if sufficiently accurate, this would eliminate the need for human evaluators to comb through hundreds of pages of medical history files. We first create a list of medical concepts, mainly …
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Concept graphs: Applications to biomedical text categorization and concept extraction
… and semantic relationships of common domain concepts. Consequently, automating learning tasks could be reinforced with those knowledge bases through constructing human-like representations of knowledge. This allows developing algorithms that simulate the human reasoning tasks of content …
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Emergency Medical Service EMR-Driven Concept Extraction From Narrative Text
… a priority. This paper presents an information extraction algorithm that custom engineers certain existing extraction techniques that work on the principles of natural language processing like metamap along with syntactic dependency parser like spacy for analyzing the sentence structure and …
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Supporting Concept Extraction and Identifier Quality Improvement through Programmers' Lexicon Analysis
… problem of program understanding focusing on (i) concept extraction, and (ii) quality of the lexicon used in identifiers. To address the first problem (concept extraction), two ontology extraction approaches exploiting the natural language information captured in identifiers and structural …
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From text mining to knowledge mining: An integrated framework of concept extraction and categorization for domain ontology
Organizations are struggling with the challenges coming from the regulatory, social and economic environment which are complex and changing continuously. They cause increase demand for the management of organizational knowledge, like how to provide employees, the necessary job-specific knowledge in …
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Learning to Improve Clinical Decisions and AI Safety by Leveraging Structure
… such as forecasting patient states, relationship extraction, disease prediction, medical report generation and differentially private model training. We begin the thesis by offering open source data processing and modeling frameworks, move towards improved interpretability of model predictions to …
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Knowledge-based methods for automatic extraction of domain-specific ontologies
… available in electronic form. However, automatic extraction of domain specific ontologies is challenging due to the unstructured nature of texts and inherent semantic ambiguities in natural language. Moreover, the large size of texts to be processed renders full-fledged natural language processing …
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Bolstering independent learning in the online age: concept-centric approaches to improving content accessibility
… impact and general applicability, we take a ``concept centric" approach to the above mentioned challenges. Concepts are the basic building blocks for any learning experience: 1) learning modules can be divided into a series of concepts discussed in the lectures, 2) from a browsing perspective, …
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Meta-level learning for the effective reduction of model search space.
… 3) adaptivity mechanism parameters, 4) recurring concept extraction, and 5) concept drift detection. The scope of this research is limited to feature engineering for problem representation, and learning strategy for algorithm and its hyper-parameters recommendation at Meta-level. There are three …