Dans le cadre des séminaires de l'axe ML et applications, le prochain séminaire sera
donné par Behrooz Omidvar-Tehrani (
http://omidvar.info/), chercheur à Amazon AI labs en
Californie.
Title: Guided Text-based Item Exploration
Speaker: Behrooz Omidvar-Tehrani, Amazon AWS AI Labs
Abstract: Users in their different roles (data owners, customers, stakeholders,
advertisers) interact with data systems to seek information. Typical information seeking
paradigms such as search and recommendation, depend on a crystal-clear definition of an
information seeking task to operate. In reality, most data-centric tasks are subjective
which require a sequence of interactions to manifest and clarify. Interacting with data
systems is a tedious task and users need to receive guided recommendations from the system
to optimize their interactions when dealing with subjectivity. In this talk, we focus on
the challenge of "subjective needs" and "multi-shot tasks", and review
(1) how the diverse and heterogeneous set of user interactions can be formalized and
represented in the form of a unique model, and (2) how data systems can leverage the
interaction model to assist users in their interactions by disambiguating their needs and
guiding users through their information seeking journey until landing on their ideal
target. We discuss real-world use cases of formalizing and learning interactions, both in
academia and industry, whose core objective is to help users interact with data systems
more effectively. We also discuss future directions of interaction learning, such as
incorporating domain knowledge and multi-environment exploration.
Speaker Bio: Behrooz is an Applied Scientist in AWS AI Labs. Prior to Amazon, he held
positions in Naver Labs Europe, the Grenoble Alpes University, and the Ohio State
University. He received his PhD in CS from the University of Grenoble Alpes, France, in
2015. His research focuses on Human-in-the-Loop Data Analytics spanning over different
research areas such as Data Mining, Databases, Visual Analytics, and Machine Learning. He
has published more than 40 papers in top-ranked international conferences and journals
including VLDB, SIGMOD, CIKM, TKDE, and CHI.
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