Modeling Interactive Information Retrieval and Social Media Interaction as Stochastic Process (Distinguished Lecture)
University of Duisburg-Essen, Germany –
Stochastic models have a long history in information retrieval (IR). For modeling sequences of interactions, different variants of Markov models have been proposed by a number of researchers. Here a user moves stochastically between different model states, which are not directly observable; instead, some signal is emitted along with each transition. For applying these models to interactive retrieval, we aim at modeling search progress at a level that is comparable to cognitive models. This allows for user-oriented analysis of interactive IR, for user guidance and for stochastic simulations of interactive IR. As a second application domain, we regard social media interaction, focusing on rumor detection and veracity in Twitter streams. Experimental results from both domains show that these approaches are well-suited for dealing with real-world data.
Norbert Fuhr holds a PhD (Dr.) in Computer Science from the Technical University of Darmstadt, which he received in 1986. He became Associate Professor in the computer science department of the University of Dortmund in 1991 and was appointed Full Professor for computer science at the University of Duisburg-Essen in 2002.
His past research dealt with topics such as probabilistic retrieval models, the integration of IR and databases, retrieval in distributed digital libraries and XML documents, and user friendly retrieval interfaces. His current research interests are models for interactive retrieval, user-oriented retrieval methods and social media retrieval.
Norbert Fuhr has served as PC member and program chair of major conferences in IR and digital libraries, and on the editorial boards of several journals in these areas.
In 2012, Norbert Fuhr received the Gerald Salton Award of ACM-SIGIR.
Mário Jorge Costa Gaspar da Silva
Mathematics, Physics & Machine Learning Seminar Series (Online)
The Mathematics, Physics & Machine Learning seminar series takes place until July 16, between 17:30 and 18:30, via Zoom.
The seminars aims to bring together mathematicians and physicists interested in machine learning (ML) with ML and AI experts interested in mathematics and physics, with the goals of introducing innovative Mathematics and Physics-inspired techniques in Machine Learning and, reciprocally, applying Machine Learning to problems in Mathematics and Physics.
Attendance is free but registration is required.
More information and the next seminars available here.
LxMLS 2020 – 10th Lisbon Machine Learning School
The 10th edition of Lisbon Machine Learning School, LxMLS, will take place from July 21st to July 29th at Instituto Superior Técnico (IST).
This event is organized by IST, Instituto de Telecomunicações (IT), INESC-ID, Unbabel, and Priberam Labs.
Applications until March 15th. For more information and to apply, access here.