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(Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2017)
Recent studies have shown that word embedding models can be used to trace time-related (diachronic) semantic shifts for particular words. In this paper, we evaluate some of these approaches on the new task of predicting ...
(Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2017)
This paper deals with using word embedding models to trace the temporal dynamics of semantic relations between pairs of words. The set-up is similar to the well-known analogies task, but expanded with a time dimension. To ...
(Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2019)
We measure the intensity of diachronic semantic shifts in adjectives in English, Norwegian and Russian across 5 decades. This is done in order to test the hypothesis that evaluative adjectives are more prone to temporal ...
(Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2019)
We extend the well-known word analogy task to a one-to-X formulation, including one-to-none cases, when no correct answer exists. The task is cast as a relation discovery problem and applied to historical armed conflicts ...
(Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2016)
This paper studies how word embeddings trained on the British National Corpus interact with part of speech boundaries. Our work targets the Universal PoS tag set, which is currently actively being used for annotation of a ...
(Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2017)
This paper describes an emerging shared repository of large-text resources for creating word vectors, including pre-processed corpora and pre-trained vectors for a range of frameworks and configurations. This will facilitate ...
(Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2018)
Recent years have witnessed a surge of publications aimed at tracing temporal changes in lexical semantics using distributional methods, particularly prediction-based word embedding models. However, this vein of research ...