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A Domain Independent Semantic Measure for Keyword Sense Disambiguation ...
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A Domain Independent Semantic Measure for Keyword Sense Disambiguation ...
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Abstract:
Understanding the user's intention is crucial for many tasks that involve human-machine interaction. To that end, word sense disambiguation (WSD) techniques play an important role. WSD techniques typically require well-formed sentences as context to operate, as well as pre-defined catalogues of word senses. However, there are some scenarios on the Web where such conditions do not apply well, such as when there is a need to disambiguate keywords from a query, or sets of tags describing any Web resource, where the context does not come as well-formed sentences. In this paper, we propose an approach to disambiguate sets of keywords by linking them to concepts of a given ontology that is not known at training time. Our approach grounds on a semantic relatedness measure between words and concepts, and explores different disambiguation algorithms to study the contribution of both word and sentence-level representations. We focus on situations where the available linguistic information is very scarce (e.g., ...
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URL: https://dx.doi.org/10.5281/zenodo.4631685 https://zenodo.org/record/4631685
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Linguistic linked data: representation, generation and applications
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Graph Exploration and Cross-lingual Word Embeddings for Translation Inference Across Dictionaries ...
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Graph Exploration and Cross-lingual Word Embeddings for Translation Inference Across Dictionaries ...
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Recent Developments for the Linguistic Linked Open Data Infrastructure ...
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Recent Developments for the Linguistic Linked Open Data Infrastructure ...
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Recent Developments for the Linguistic Linked Open Data Infrastructure ...
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Recent Developments for the Linguistic Linked Open Data Infrastructure ...
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Recent Developments for the Linguistic Linked Open Data Infrastructure ...
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Proceedings of the LREC 2020 7th Workshop on Linked Data in Linguistics ...
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