Results 31 to 40 of about 96,400 (324)
AutoExtend: Combining Word Embeddings with Semantic Resources
Computational Linguistics, 2017 We present AutoExtend, a system that combines word embeddings with semantic resources by learning embeddings for non-word objects like synsets and entities and learning word embeddings that incorporate the semantic information from the resource.
Sascha Rothe, Hinrich Schütze
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Benchmark for Evaluation of Danish Clinical Word Embeddings
Northern European Journal of Language Technology, 2023 In natural language processing, benchmarks are used to track progress and identify useful models. Currently, no benchmark for Danish clinical word embeddings exists.
Martin Sundahl Laursen +4 more
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Morphological Skip-Gram: Replacing FastText characters n-gram with morphological knowledge
Inteligencia Artificial, 2021 Natural language processing systems have attracted much interest of the industry. This branch of study is composed of some applications such as machine translation, sentiment analysis, named entity recognition, question and answer, and others.
Thiago Dias Bispo +3 more
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Socialized Word Embeddings [PDF]
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017 Word embeddings have attracted a lot of attention. On social media, each user’s language use can be significantly affected by the user’s friends. In this paper, we propose a socialized word embedding algorithm which can consider both user’s personal characteristics of language use and the user’s social relationship on social media.
Ziqian Zeng +3 more
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A Collection of Swedish Diachronic Word Embedding Models Trained on Historical Newspaper Data
Journal of Open Humanities Data, 2021 This paper describes the creation of several word embedding models based on a large collection of diachronic Swedish newspaper material available through Språkbanken Text, the Swedish language bank.
Simon Hengchen, Nina Tahmasebi
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Biomedical Word Sense Disambiguation with Word Embeddings [PDF]
, 2017 There is a growing need for automatic extraction of information and knowledge from the increasing amount of biomedical and clinical data produced, namely in textual form. Natural language processing comes in this direction, helping in tasks such as information extraction and information retrieval.
Antunes, Rui, Matos, Sérgio
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A Gloss Composition and Context Clustering Based Distributed Word Sense Representation Model
Entropy, 2015 In recent years, there has been an increasing interest in learning a distributed representation of word sense. Traditional context clustering based models usually require careful tuning of model parameters, and typically perform worse on infrequent word ...
Tao Chen +3 more
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Efficient estimation of Hindi WSD with distributed word representation in vector space
Journal of King Saud University: Computer and Information Sciences, 2022 Word Sense Disambiguation (WSD) is significant for improving the accuracy of the interpretation of a Natural language text. Various supervised learning-based models and knowledge-based models have been developed in the literature for WSD of the language ...
Archana Kumari, D.K. Lobiyal
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When FastText Pays Attention: Efficient Estimation of Word Representations using Constrained Positional Weighting [PDF]
Journal of Universal Computer Science, 2022 In 2018, Mikolov et al. introduced the positional language model, which has characteristics of attention-based neural machine translation models and which achieved state-of-the-art performance on the intrinsic word analogy task.
Vít Novotný +4 more
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Embeddings for word sense disambiguation: an evaluation study [PDF]
, 2016 Recent years have seen a dramatic growth in the popularity of word embeddings mainly owing to their ability to capture semantic information from massive amounts of textual content.
Iacobacci, IGNACIO JAVIER +2 more
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