The core meanings: semantic properties of performance
Exploring Semantic Properties of Sentence Embeddings
... b) ”We made our own decision,” he said. — ”We didn’t make our own decision,” he said. — We made our own decision. For cases resembling a), the average SkipThought similarity between the sentence and its Not-Negation ...
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Drug prioritization using the semantic properties of a knowledge graph
... the semantic information between drug and disease concepts as features, which are extracted from an existing knowledge graph that integrates 200 different biological knowledge ...cross-validation ...
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Drug prioritization using the semantic properties of a knowledge graph
... the semantic information between drug and disease concepts as features, which are extracted from an existing knowledge graph that integrates 200 different biological knowledge ...cross-validation ...
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Drug prioritization using the semantic properties of a knowledge graph
... the semantic information between drug and disease concepts as features, which are extracted from an existing knowledge graph that integrates 200 different biological knowledge ...cross-validation ...
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MayoClinicNLP–CORE: Semantic representations for textual similarity
... Competition performance Table 2 shows the top 10 runs of 90 submitted in the STS-Core task are shown, with our three sys- tems placing 5th, 6th, and ...
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Core vocabularies and their role in promoting semantic interoperability
... ISA Core Vocabularies to include properties and relationships needed by local administrations in Flanders, like family composition or persons acting on behalf of a registered ...
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A Probabilistic Model of Syntactic and Semantic Acquisition from Child Directed Utterances and their Meanings
... The learner then has to infer the meanings and syntactic properties of the words in the input along with a parsing model. We use the CCG grammatical framework and train a non-parametric Bayesian model of ...
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SemEval-2016 Task~10: Detecting Minimal Semantic Units and their Meanings (DiMSUM)
... lexical semantic representation (§2, §3) has been annotated in an extensive bench- mark data set comprising several nontraditional do- mains ...in performance, all are below 60% in our composite evaluation, ...
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YAGO: A Core of Semantic Knowledge Unifying WordNet and Wikipedia
... Such an ontology would have to be of high quality, with ac- curacy close to 100 percent, i.e. comparable in quality to an encyclopedia. It would have to comprise not only con- cepts in the style of WordNet, but also ...
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UMBC EBIQUITY CORE: Semantic Textual Similarity Systems
... tested performance of the align-and-penalize approach on all of the 2012 STS ...The performance of the approach without using the antonym penalty is also tested, producing correlation scores of ...
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UNIBA CORE: Combining Strategies for Semantic Textual Similarity
... Distributional semantic models In several features proposed in our approaches, the similarity between words is computed using Dis- tributional Semantic ...word meanings through contexts: the ...
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Semantic process mining tools: core building blocks
... 4 SEMANTIC PROCESS MINING The aim of semantic process mining is to make use of the semantics of the data captured in event logs to, on the one hand, create new techniques or enhance existing ones to better ...
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Enhancing the performance of multi-modality ontology semantic image retrieval using object properties filter
... retrieval performance to get more accu- rate ...retrieval performance has improved for about 5 to 30 percent by combining the high-level textual information with low-level image features and introducing the ...
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High Performance Descriptive Semantic Analysis of Semantic Graph Databases
... As semantic graph database technology grows to address components ranging from large triple stores to SPARQL endpoints over SQL-structured relational databases, it will become increasingly impor- tant to be able ...
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Core Semantic First: A Top down Approach for AMR Parsing
... The core semantic first prin- ciple emphasizes capturing the main ideas of a sentence, which is of great ...state-of-the-art performance in the sense that no heuristic graph re-categorization is ...
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CNGL CORE: Referential Translation Machines for Measuring Semantic Similarity
... the performance of transla- tion, judging the semantic similarity between text, and evaluating the quality of student ...good performance are applicable across different domains and ...
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CNGL-CORE: Referential translation machines for measuring semantic similarity
... the semantic similarity between text. RTMs make quality and semantic similarity judgments possible by using retrieved rele- vant training data as interpretants for reach- ing shared ...translation ...
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Evaluating the performance of the OntoSem semantic analyzer
... Figure 4. Gold Standard Syntactic Analysis for a sample sentence. TMR element in the semantics being evaluated. Each property modifying the gold standard TMR element that is also in the evaluation TMR element increments ...
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CPN CORE: A Text Semantic Similarity System Infused with Opinion Knowledge
... of semantic informa- tion from ...high performance on more than five of the ...the performance attained by other knowledge-based measures, despite its com- putational ...
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Search with Meanings: An Overview of Semantic Search Systems
... 2. Semantic Search Systems Conventional search techniques are developed on the basis of words computation model and enhanced by the link ...hand, semantic search extends the scope of traditional information ...
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