Ondrej Proksa

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Media content recommendation is nowadays a common problem. Traditional algorithms based on collaborative filtering require an up-to-date dataset of users and their preferences, which is difficult to gather for huge database of items. Content-based approach suffers from the complex computation of similarity among items. In this paper we propose an approach(More)
Large amount of entities published by various sources inevitably introduces inaccuracies, mainly duplicated information. These can even be found within a single dataset. In this paper we propose a method for automatic discovery of identity relationship between two entities (also known as instance matching) in a dataset represented as a graph (e.g. in the(More)
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