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Dimensions of Commonsense Knowledge
Commonsense knowledge is essential for many AI applications, including t...
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Exploring and Analyzing Machine Commonsense Benchmarks
Commonsense question-answering (QA) tasks, in the form of benchmarks, ar...
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Explanation Ontology: A Model of Explanations for User-Centered AI
Explainability has been a goal for Artificial Intelligence (AI) systems ...
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Explanation Ontology in Action: A Clinical Use-Case
We addressed the problem of a lack of semantic representation for user-c...
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Directions for Explainable Knowledge-Enabled Systems
Interest in the field of Explainable Artificial Intelligence has been gr...
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Foundations of Explainable Knowledge-Enabled Systems
Explainability has been an important goal since the early days of Artifi...
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Making Study Populations Visible through Knowledge Graphs
Treatment recommendations within Clinical Practice Guidelines (CPGs) are...
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Semantically-aware population health risk analyses
One primary task of population health analysis is the identification of ...
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Knowledge Integration for Disease Characterization: A Breast Cancer Example
With the rapid advancements in cancer research, the information that is ...
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Seq2RDF: An end-to-end application for deriving Triples from Natural Language Text
We present an end-to-end approach that takes unstructured textual input ...
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Exploiting Task-Oriented Resources to Learn Word Embeddings for Clinical Abbreviation Expansion
In the medical domain, identifying and expanding abbreviations in clinic...
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From Data to City Indicators: A Knowledge Graph for Supporting Automatic Generation of Dashboards
In the context of Smart Cities, indicator definitions have been used to ...
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Human-Aware Sensor Network Ontology: Semantic Support for Empirical Data Collection
Significant efforts have been made to understand and document knowledge ...
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Contextual Data Collection for Smart Cities
As part of Smart Cities initiatives, national, regional and local govern...
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