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Machine Learning for User modeling: A State of the Art

Abstract

A fundamental objective of human-computer interaction research isto make systems more usable, more useful, and to provide users with experi-ences fitting their specific background, knowledge and objectives. Specifically, today we want systems to do the 'right' thing at the'right' time in the' right' way. Designers of human-computer systems face the formidable task of writing soft-ware for millions of users (at design time) while making it work as if it were designed for each individual user (only known at use time). User modeling research has attempted to address these issues. In this article, I will provide anassessment of the current state of the art, a review of all the main researchesthat have been conducted in the field and its main tracks, essentially based on the papers submitted and accepted to the ACM UMAP international conference, which is the premier international conference dedicated to the subject of user modeling. A special emphasis is given to machine learning algorithms used to tackle challenges encountered in the field.

Contents

  • A scientific article : and its latex source code -> report sub directory
  • Workshops in the form of jupyter notebooks -> workshops sub directory

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