Przemysław Kazienko
Wrocław University of Technology
257 Papers
1.6K Citations
Przemysław Kazienko is an academic researcher from Wrocław University of Technology. The author has contributed to research in topics: Social network & Computer science. The author has an hindex of 33, co-authored 236 publications. Previous affiliations of Przemysław Kazienko include University of Wrocław.
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Papers
Consumer Wearables and Affective Computing for Wellbeing Support
Stanisław Saganowski,Przemysław Kazienko,Maciej Dziezyc,Patrycja Jakimów,Joanna Komoszynska,Weronika Michalska,Anna Dutkowiak,Adam G. Polak,Adam Dziadek,Michal Ujma +9 more
- 07 Dec 2020
TL;DR: In this article, the WellAff system was proposed to recognize affective states for wellbeing support in patients suffering from bipolar disorder, in particular patients with chronic kidney disease and bipolar disorder.
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A Generic Model for a Multidimensional Temporal Social Network
Przemysław Kazienko,Elżbieta Kukla,Katarzyna Musial,Tomasz Kajdanowicz,Piotr Bródka,Jarosław Gaworecki +5 more
- 03 Aug 2011
TL;DR: A comprehensive generic model for a multidimensional, temporal social network that covers three main dimensions: layers, time windows and social groups is proposed in the paper.
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Comparison of the Efficiency of MapReduce and Bulk Synchronous Parallel Approaches to Large Network Processing
Tomasz Kajdanowicz,Wojciech Indyk,Przemysław Kazienko,Jakub Kukul +3 more
- 10 Dec 2012
TL;DR: Two parallel approaches to process large graph structures within the Hadoop environment were compared and revealed that iterative graph processing with BSP implementation significantly outperform popular MapReduce, especially for algorithms with many iterations and sparse communication.
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Aspect Detection using Word and Char Embeddings with (Bi)LSTM and CRF
TL;DR: The authors proposed a new accurate aspect extraction method that makes use of both word and character-based embeddings and obtained state-of-the-art F-score results for SemEval Restaurants (85%) and Laptops (80%).
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•Posted Content
Group Evolution Discovery in Social Networks
TL;DR: The new method for the group evolution discovery called GED is proposed in this paper and the results of the first experiments on the email based social network together with comparison with two other methods of group evolutioniscovery are presented.
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