László Grad-Gyenge

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The BRUniBP team’s submission is presented for the Discriminating between Similar Languages Shared Task 2015. Our method is a two phase classifier that utilizes both character and word-level features. The evaluation shows 100% accuracy on language group identification and 93.66% accuracy on language identification. The main contribution of the paper is a(More)
Teamwork plays an important role in many areas of today's society, such as business activities. Thus, the question of how to form an effective team is of increasing interest. In this paper we use the team-oriented multiplayer online game Dota 2 to study cooperation within teams and the success of teams. Making use of game log data, we choose a statistical(More)
This paper presents a novel, graph embedding based recommendation technique. The method operates on the knowledge graph, an information representation technique alloying content-based and collaborative information. To generate recommendations, a two dimensional embedding is developed for the knowledge graph. As the embedding maps the users and the items to(More)
This paper presents the analysis on the optimal settings of the spreading parameters of the spreading activation technique. The method is applied on the knowledge graph, an information representation technique that combines collaborative and content-based information. The evaluation of the recommendation technique is based on recommendation lists. The(More)
We present a conceptual approach in the field of recommender systems, which is intended to model human consumption by maintaining a network of heterogeneous nodes and relationships. We think of this model as the reflection of the corresponding cognitive functionality of human thinking, as we maintain a structure which is similar to the structures(More)
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