Veronika Bogina

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Predicting whether a session is a buying session (e.g. will end with buying an item) is an ongoing research task. Drawing from recent experience in Web search and movie recommenders, we explore the effect of temporal trends and characteristics on the ability to predict buying sessions. We suggest a new approach, based on items' temporal dynamics, together(More)
User Adaptive Systems (UASs) are futile without software. Moreover, integrating user modeling component into software system may add bugs if not tested properly. However, the evaluation of UASs does not intersect with software evaluation as commonly defined in Software Engineering. We suggest adopting the common software engineering practices, changing the(More)
The workshop focus is on considering temporal aspects for recommender systems in general, regardless of the specific domain and application, trying to develop a holistic approach for dealing with temporal aspects in recommender systems, like personal assistants, news, tourism, health care, TV, e-commerce, social networks and so on.
Early studies about user modeling already noted that user models need to continuously adapt, as new information about the user becomes available, keeping the user model updated. Although temporal aspects are inherent characteristics of user modeling, so far, they were not specifically dealt with. Therefore, the proposed research will suggest an abstract,(More)
Recurrent Neural Networks (RNN) is a frequently used technique for sequence data predictions. Recently, it gains popularity in the Recommender Systems domain, especially for session-based recommendations where naturally, each session is defined as a sequence of clicks, and timestamped data per click is available. In our research, in its early stages, we(More)
The importance of user modeling and personalization is taken for granted in several scenarios. According to this widespread paradigm, each user can be modeled through some (explicitly or implicitly gathered) information about her knowledge or about her preferences, in order to adapt the behavior of a generic intelligent system to her specific(More)
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