Seminar om forsking, innovasjon og teknologi
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Session-based Recommendation: Challenges and Recent Advances
November 23, 2018. Tid: 10:15 - 12:00Free
Recommender systems is an applied AI technique that we often meet when surfing the web. In many applications of such systems, a larger fraction of the user population are first-time users or are not logged in when they use the service. In these cases, the item suggestions by the recommender cannot be based on individual long-term preference profiles. Instead, the recommendations have to be determined based on the observed short-term behavior of the users. Due to the high practical relevance of session-based recommendation, different proposals were made in recent years to deal with the particular challenges of the problem setting, among them deep neural networks. In this talk we will review some of these challenges and provide a survey on recent advances in the field. A specific focus on the talk will be on the particularities of the e-commerce domain.
Dietmar Jannach is a full professor of Information Systems at AAU Klagenfurt, Austria. Before joining AAU in 2017, he was a professor of Computer Science at TU Dortmund, Germany. In his research, he focuses on the application of intelligent system technology to practical problems and the development of methods for building knowledge-intensive software applications. In the last years, Dietmar Jannach worked on various practical aspects of recommender systems. He is the main author of the first textbook on the topic published by Cambridge University Press in 2010 and was the co-founder of a tech startup that created an award-winning product for interactive advisory solutions.