Zobrazeno 1 - 6
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pro vyhledávání: '"Malgorzata Marciniak"'
Publikováno v:
Terminology. 21:180-204
Domain corpora are often not very voluminous and even important terms can occur in them not as isolated maximal phrases but only within more complex constructions. Appropriate recognition of nested terms can thus influence the content of the extracte
Publikováno v:
Cognitive Studies | Études cognitives, Vol 0, Iss 17 (2017)
Testing word embeddings for PolishDistributional Semantics postulates the representation of word meaning in the form of numeric vectors which represent words which occur in context in large text data. This paper addresses the problem of constructing
Publikováno v:
Nonimaging Optics: Efficient Design for Illumination and Solar Concentration XIV.
The purpose of this study is to analyze various surfaces of flexible solar panels and compare them to the traditional at panels mathematically. We evaluated the efficiency based on the integral formulas that involve flux. We performed calculations fo
Autor:
Malgorzata Marciniak
Publikováno v:
Malgorzata Marciniak
This article describes the Hartogs and the Hartogs–Bochner extension phenomena in smooth toric surfaces and the connection with the first cohomology group with compact support. The affirmative and negative results are proved using topological, anal
Publikováno v:
Nonstandard Analysis for the Working Mathematician ISBN: 9789401773263
The intuitive notion of forming a compactification of a topological space is to “attach” new points to a space to “compactify” it. We use equivalence relations on the remote points of an enlargement of a given topological space to produce the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e9ed0ed0388af34e6320a2724163a5a5
https://doi.org/10.1007/978-94-017-7327-0_5
https://doi.org/10.1007/978-94-017-7327-0_5
Publikováno v:
Proceedings of the 4th International Workshop on Computational Terminology (Computerm).
In the paper, we propose a new method of identifying terms nested within candidates for the terms extracted from domain texts. The list of all terms is then ranked by the process of automatic term recognition. Our method of identifying nested terms i