Распределительные семантические модели

. Systematic cross-linguistic studies of verbs syntactic-semantic behaviors for ty- pologically distant languages such as Mandarin Chinese and French are difficult to conduct. Such studies are nevertheless necessary due to …...

AbstractDistributional semantic models have been effective at representing linguistic semantics at the word level, and more recently research has moved on to the construction of distributional representations for larger segments …...

Distributional semantic models (DSMs) have been effective at representing seman- tics at the word level, and research has re- cently moved on to building distributional representations for larger segments of …...

This paper describes the UNIBA team participation in the Cross-Level Semantic Similarity task at SemEval 2014. We pro- pose to combine the output of different se- mantic similarity measures which …...

This paper discusses the use of factoriza- tion techniques in distributional semantic models. We focus on a method for re- distributing the weight of latent variables, which has previously been …...

AbstractThis paper aims to implement what is referred to as the collocation of the Arabic keywords approach for extracting formulaic sequences (FSs) in the form of high frequency but semantically …...

AbstractDespite the recent success of distributional semantic models (DSMs) in various semantic tasks they remain disconnected with real-world perceptual cues since they typically rely on linguistic features. Text data constitute …...

AbstractDistributional semantic models (DSMs) are currently being used in the measurement of word relatedness and word similarity. One shortcoming of DSMs is that they do not provide a principled way …...

AbstractHuman concept representations are often grounded with visual information, yet some aspects of meaning cannot be visually represented or are better described with language. Thus, vision and language provide complementary …...

Distributional semantic models (DSMs) are often evaluated on artificial simi- larity datasets containing single words or fully compositional phrases. We present a large-scale multilingual eval- uation of DSMs for predicting …...

This paper investigates the effects of data size and frequency range on distributional seman- tic models. We compare the performance of a number of representative models for several test settings …...

AbstractEmojis allow us to describe objects, situations and even feelings with small images, providing a visual and quick way to communicate. In this paper, we analyse emojis used in Twitter …...

Distributional semantic models can pre- dict many linguistic phenomena, including word similarity, lexical ambiguity, and se- mantic priming, or even to pass TOEFL synonymy and analogy tests (Landauer and Dumais, …...

AbstractRecent studies of distributional semantic models have set up a competition between word embeddings obtained from predictive neural networks and word vectors obtained from abstractive count-based models. This paper is …...

AbstractThe fundamental role of hypernymy in NLP has motivated the development of many methods for the automatic identification of this relation, most of which rely on word distribution. We investigate …...

In recent years word embedding/distributional semantic models evolved to become a fundamental component in many natural language processing (NLP) architectures due to their ability of capturing and quantifying semantic associations …...

Distinguishing lexical relations has been a long term pursuit in natural language processing (NLP) domain. Recently, in order to detect lexical relations like hypernymy, meronymy, co-hyponymy etc., distributional semantic models …...

AbstractIn this work, we address the evaluation of distributional semantic models trained on smaller, domain-specific texts, specifically, philosophical text. Specifically, we inspect the behaviour of models using a pre-trained background …...

AbstractThe compositionality degree of multiword expressions indicates to what extent the meaning of a phrase can be derived from the meaning of its constituents and their grammatical relations. Prediction of …...

AbstractComputational linguistic research on language change through distributional semantic (DS) models has inspired researchers from fields such as philosophy and literary studies, who use these methods for the exploration and …...

AbstractLexical Semantic Change is the study of how the meaning of words evolves through time. Another related question is whether and how lexical relations over pairs of words, such as …...