'User models' diaporamas de présentation

A journey through some of the research projects at the Knowledge Discovery & Web Mining Lab at Univ. of Louisville

A journey through some of the research projects at the Knowledge Discovery & Web Mining Lab at Univ. of Louisville. Olfa Nasraoui Dept . of Computer Engineering & Computer Science Speed School of Engineering, University of Louisville Contact e-mail: olfa.nasraoui@louisville.edu.

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CSA3212: User-Adaptive Systems

CSA3212: User-Adaptive Systems. Topic 5: User Modelling. Dr. Christopher Staff Department of Intelligent Computer Systems University of Malta. Aims and Objectives. Background to user modelling User model implementations Types of user model Understanding user behaviour. Part I: Background.

971 views • 78 slides

Information Filtering / Personalization

Information Filtering / Personalization. Luz M. Quiroga Stimulate 2005. Information Filtering (IF) / Personalization. What do we understand for IF? How different is IF from IR Why do we might need it? What personalization means to you? Do you make use of it? For what purpose?.

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TG09 Gateway Face to Face

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Introduction to Usability Engineering

Introduction to Usability Engineering. Laura Leventhal and Julie Barnes. Sources. Chapter 1, Protobook. Motivation for this Unit. When you are finished with the introduction (lectures 1 - 3), you should be able to :

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Exploring the role of affective feedback in Interactive IR

Exploring the role of affective feedback in Interactive IR. Joemon M Jose (with Ioannis Arapakis & Ioannis Konstas) Department of Computing Science. Questions?. What is the role of emotions in the information seeking process? Do they correspond to any form of relevance feedback?

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User Profile ontology with social network and historical records elements

User Profile ontology with social network and historical records elements. Anatoliy Kim. Table of Contents. Introduction Motivation Goal Related Works User Profile Ontology Modelling User Modelling User Context Contribution Algorithm Usage scenario Tools Inferring and rating

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Scientific Workflow Requirements

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Leveraging ... User Models

Leveraging ... User Models. Leveraging Data About Users in General in the Learning of Individual User Models* Anthony Jameson PhD (Psychology) Adjunct Professor of HCI Frank Wittig CS Researcher Saarland University, Saarbrucken Germany * i.e. pooling knowledge to improve learning accuracy.

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Third Generation Adaptive Hypermedia Systems

Third Generation Adaptive Hypermedia Systems. Curtis A. Carver Jr., John M.D. Hill and Udo W. Pooch. Agenda. Introduction Background First Generation Adaptive Hypermedia Systems Second Generation AHS Third Generation AHS Multi-dimensional User Models Finely Grained Multimedia Adaptation

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User Modeling for Personalized City Tours

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Formal Notations and Tools for addressing both Safety and Usability concerns for Interactive Systems

Formal Notations and Tools for addressing both Safety and Usability concerns for Interactive Systems. Philippe Palanque LIIHS-IRIT University Paul Sabatier Toulouse - France. Overview of LIIHS-IRIT (1). Research themes Software Engineering for Human-Computer Interaction

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Customizable Bayesian Collaborative Filtering

Customizable Bayesian Collaborative Filtering. Denver Dash Big Data Reading Group 11/19/2007. Why Work on Recommender Systems?. Generally: Widespread interest from different industries. Marketers save time/money by advertising to the right people.

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Leveraging ... User Models

Leveraging ... User Models. Leveraging Data About Users in General in the Learning of Individual User Models* Anthony Jameson PhD (Psychology) Adjunct Professor of HCI Frank Wittig CS Researcher Saarland University, Saarbrucken Germany *pooling knowledge to improve learning accuracy.

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emotions

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ISE 412: Human Factors Engineering

ISE 412: Human Factors Engineering. Dr. Laura Moody Fall, 2008. Course Goals. Upon completion of ISE 412, students will be able to: Develop, conduct, and evaluate the results of human factors research. Develop models of human-machine systems.

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Introduction

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Data search & distribution

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Introduction

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