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(Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2017)
This paper describes the process of automatically adding synsets and hypernymy relations to an existing wordnet based on word embeddings computed for POStagged lemmas in a large news corpus, achieving exact match attachment ...
(Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2018)
In this paper, we empirically evaluate the utility of transfer and multi-task learning on a challenging semantic classification task: semantic interpretation of noun--noun compounds. Through a comprehensive series of ...
(Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2018)
This paper presents the Norwegian Review Corpus (NoReC), created for training and evaluating models for document-level sentiment analysis. The full-text reviews have been collected from major Norwegian news sources and ...
(Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2019)
Neural methods for sentiment analysis have led to quantitative improvements over previous approaches, but these advances are not always accompanied with a thorough analysis of the qualitative differences. Therefore, it is ...
(Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2019)
This paper explores the use of multi-task learning (MTL) for incorporating external knowledge in neural models. Specifically, we show how MTL can enable a BiLSTM sentiment classifier to incorporate information from sentiment ...
(Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2019)
This paper documents the creation of a large-scale dataset of evaluative sentences – i.e. both subjective and objective sentences that are found to be sentiment-bearing – based on mixed-domain professional reviews from ...
(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 ...