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Now showing items 1-10 of 18
(Chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2013)
This paper documents ongoing work within the Norwegian CLARINO project on building a Language Analysis Portal (LAP). The portal will provide an intuitive and easily accessible web interface to a centralized repository of ...
(Chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2013)
This demonstration presents a first operable pilot of the Language Analysis Portal (LAP), an ongoing project within the Norwegian CLARINO initiative that aims at providing easy access to Language Technology (LT) tools ...
(Chapter / Bokkapittel / PublishedVersion; Peer reviewed, 2015)
This paper describes a semi-supervised approach to improving statistical dependency parsing using dependency-based word clusters. After applying a baseline parser to unlabeled text, clusters are induced using K-means with ...
(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 ...
(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, 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, 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)
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 ...