Michal Lopuszynski

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In this work, we compare two simple methods of tagging scientific publications with labels reflecting their content. As a first source of labels Wikipedia is employed, second label set is constructed from the noun phrases occurring in the analyzed corpus. We examine the statistical properties and the effectiveness of both approaches on the dataset(More)
In this work, two simple methods of tagging scientific publications with labels reflecting their content are presented and compared. As a first source of labels, Wikipedia is employed. A second label set is constructed from the noun phrases occurring in the analyzed corpus. The corpus itself consists of abstracts from 0.7 million scientific documents(More)
[4] M. Jungiewicz, M. Łopuszyński, Unsupervised keyword extraction from Polish legal texts, In Advances in NLP, 65–70, Springer (2014) [5] M. Łopuszyński, Ł. Bolikowski, Towards robust tags from NLP tools and Wikipedia, Int. Journal of Digit. Libraries (2015) (available online) I acknowledge the support from the SAOS project financed by the National Centre(More)
In this work we present a detailed computational study of the structural and elastic properties of cubic Al(x)Ga(y)In(1 - x - y)N alloys in the framework of the Keating valence force field model, for which we perform an accurate parametrization based on state-of-the-art density functional theory calculations. When analysing structural properties, we focus(More)
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