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of 36
pro vyhledávání: '"Brychcín, Tomáš"'
We generalize the word analogy task across languages, to provide a new intrinsic evaluation method for cross-lingual semantic spaces. We experiment with six languages within different language families, including English, German, Spanish, Italian, Cz
Externí odkaz:
http://arxiv.org/abs/1807.04175
Autor:
Brychcín, Tomáš
Cross-lingual semantic textual similarity systems estimate the degree of the meaning similarity between two sentences, each in a different language. State-of-the-art algorithms usually employ machine translation and combine vast amount of features, m
Externí odkaz:
http://arxiv.org/abs/1807.04172
Autor:
Brychcín, Tomáš, Král, Pavel
This paper introduces a new unsupervised approach for dialogue act induction. Given the sequence of dialogue utterances, the task is to assign them the labels representing their function in the dialogue. Utterances are represented as real-valued vect
Externí odkaz:
http://arxiv.org/abs/1612.06572
Autor:
Svoboda, Lukáš, Brychcín, Tomáš
The word embedding methods have been proven to be very useful in many tasks of NLP (Natural Language Processing). Much has been investigated about word embeddings of English words and phrases, but only little attention has been dedicated to other lan
Externí odkaz:
http://arxiv.org/abs/1608.00789
Autor:
Brychcin, Tomas
In this paper we introduce Latent Tree Language Model (LTLM), a novel approach to language modeling that encodes syntax and semantics of a given sentence as a tree of word roles. The learning phase iteratively updates the trees by moving nodes accord
Externí odkaz:
http://arxiv.org/abs/1607.07057
Publikováno v:
In Expert Systems With Applications 30 November 2019 135:287-295
Autor:
Taylor Stephen, Brychcín Tomáš
Publikováno v:
Open Computer Science, Vol 8, Iss 1, Pp 182-193 (2018)
We demonstrate several ways to use morphological word analogies to examine the representation of complex words in semantic vector spaces. We present a set of morphological relations, each of which can be used to generate many word analogies. 1. We sh
Externí odkaz:
https://doaj.org/article/818d5a0d53cb4c64ac77ac8a7aba6c43
Autor:
Brychcín, Tomáš, Konopík, Miloslav
Publikováno v:
In Computer Speech & Language September 2015 33(1):88-108
Publikováno v:
In Expert Systems With Applications 1 May 2015 42(7):3470-3479