Hashtag the Tweets: Experimental Evaluation of Semantic Relatedness Measures
نویسندگان
چکیده
منابع مشابه
Exploiting Semantic Relatedness Measures for Multi-label Classifier Evaluation
In the multi-label classification setting, documents can be labelled with a number of concepts (instead of just one). Evaluating the performance of classifiers in this scenario is often as simple as measuring the percentage of correctly assigned concepts. Classifiers that do not retrieve a single concept existing in the ground truth annotation are all considered equally poor. However, some clas...
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Rich data provided by tweets have been analyzed, clustered, and explored in a variety of studies. Typically those studies focus on named entity recognition, entity linking, and entity disambiguation or clustering. Tweets and hashtags are generally analyzed on sentential or word level but not on a compositional level of concatenated words. We propose an approach for a closer analysis of compound...
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The automatic ranking of word pairs as per their semantic relatedness and ability to mimic human notions of semantic relatedness has widespread applications. Measures that rely on raw data (distributional measures) and those that use knowledge-rich ontologies both exist. Although extensive studies have been performed to compare ontological measures with human judgment, the distributional measur...
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Measures of semantic similarity between concepts are widely used in Natural Language Processing. In this article, we show how six existing domain-independent measures can be adapted to the biomedical domain. These measures were originally based on WordNet, an English lexical database of concepts and relations. In this research, we adapt these measures to the SNOMED-CT ontology of medical concep...
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ژورنال
عنوان ژورنال: International Journal of Advanced Computer Science and Applications
سال: 2016
ISSN: 2156-5570,2158-107X
DOI: 10.14569/ijacsa.2016.070662