Our position paper called “Poisson Factorization Models for Spatiotemporal Retrieval”, joint work with Dirk Ahlers, got accepted at the 11th Workshop on Geographic Information Retrieval (GIR’17). In this work, we discuss some modelling ideas and possibilities for advancing spatiotemporal retrieval using Poisson factorization models, especially in scenarios where we have multiple sources of count or implicit spatiotemporal user data. Unfortunately, I will not be able to attend the workshop (but Dirk will be there), because I am now in Melbourne, Australia, and will stay here for 3 months, participating as visiting graduate student in a project with the IR group at RMIT. In particular, I will be working with Dr Yongli Ren and Prof Mark Sanderson, developing joint probabilistic models for spatiotemporal user data for indoor spaces recommendations (they have a very interesting dataset that I am curious to explore). Hopefully, in the next couple of months, I will continue working on nice probabilistic models for recommender system, but incorporating many new and interesting ideas related to location and time.
Published by Eliezer Silva (zehsilva)
Researcher and engineer. Interested in Machine Learning, probabilistic models, mathematical modeling and many other applications of computational thinking. Also sometimes like to get a bit into politics and philosophy. View all posts by Eliezer Silva (zehsilva)