Implicit and Explicit User Modelling Techniques for Interactive Visual Knowledge Exploration
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Implicit and Explicit User Modelling Techniques for Interactive Visual Knowledge Exploration by Thomas Johannes Hengster Dissertation Presented to the University of Dublin, Trinity College in fulfillment of the requirements for the Degree of Master of Science in Computer Science University of Dublin, Trinity College September 2009 Declaration I, the undersigned, declare that this work has not previously been submitted as an exercise for a degree at this, or any other University, and that unless otherwise stated, is my own work. ________________________________________ Thomas Johannes Hengster 3rd September 2009 Permission to lend and/or copy I, the undersigned, agree that Trinity College Library may lend or copy this thesis upon request. ________________________________________ Thomas Johannes Hengster 3rd September 2009 Acknowledgments I would like to thank my supervisor Dr. Owen Conlan for his patience, invaluable assistance and guidance during the course of this project. Further I would like to thank Cormac Hampson for his constant support, advice and time. I also would like to thank my family for all the encouragement throughout the last year. Finally, I would like to thank everyone from the Networks and Distributed Systems course. Keep up the good work! Thomas Johannes Hengster University of Dublin, Trinity College September 2009 iv Abstract This work investigates the challenges when modelling a user's intent as he interactively explores a knowledge space and correlating it with subjective expertise about that space. As this exploration is visual in nature the user is not burdened with unnecessary modelling and information seeking concerns in order to maintain flow and immersion. A balance between explicit and implicit modelling techniques needs to be maintained to ensure the user has a contiguous experience. Furthermore it offers an alternative to collaborative filtering. It does not rely on peer ratings, but independently draws conclusions from continuous user interactions with the system. As a result, it does not suffer from missing or incorrect pre compiled facts and correlations. Nor does it suffer from the sparsity problem that many collaborative filtering systems exhibit. The personalised nature of the interactions and the user’s subsequent discoveries presents a need for detailed, yet potentially quickly changing user models. This also requires carefully balancing and throttling the influence of related semantic attributes. v Table of Contents Acknowledgments ................................................................................................................................... iv Abstract.......................................................................................................................................................... v List of Tables ................................................................................................................................................ x List of Figures ............................................................................................................................................ xi 1 Introduction ...................................................................................................................................... 1 1.1 Overview ..................................................................................................................................... 1 1.2 Motivation .................................................................................................................................. 1 1.3 Research Statement ................................................................................................................ 3 1.3.1 Objectives and Goals ...................................................................................................... 3 1.4 Approach .................................................................................................................................... 4 1.5 Proposed Contribution .......................................................................................................... 5 1.6 Thesis Structure ....................................................................................................................... 5 2 State of the Art .................................................................................................................................. 7 2.1 Overview ..................................................................................................................................... 7 2.2 KDDM, Flexible Querying and Dataspaces ..................................................................... 7 2.3 SARA ............................................................................................................................................. 9 2.3.1 Process Model .................................................................................................................. 9 2.3.2 Semantic Attributes ..................................................................................................... 11 2.4 User Modelling and Personalisation .............................................................................. 12 2.5 Film Recommendation Services ...................................................................................... 14 2.5.1 The Internet Movie Database ................................................................................... 14 2.5.2 Rotten Tomatoes ........................................................................................................... 16 2.5.3 Amazon ............................................................................................................................. 17 2.5.4 MovieLens........................................................................................................................ 18 2.5.5 What to Rent ................................................................................................................... 19 2.5.6 Criticker ............................................................................................................................ 21 vi 2.5.7 Clerkdogs ......................................................................................................................... 21 2.5.8 Jinni .................................................................................................................................... 23 2.5.9 Summary .......................................................................................................................... 24 2.6 Visualisation Techniques ................................................................................................... 25 2.6.1 Cooliris .............................................................................................................................. 26 2.6.2 Newsmap ......................................................................................................................... 27 2.6.3 Stacked Graphs .............................................................................................................. 28 2.6.4 Musicovery ...................................................................................................................... 29 2.6.5 FIDGT ................................................................................................................................. 30 2.6.6 Summary .......................................................................................................................... 31 2.7 Conclusion ................................................................................................................................ 32 3 Design ................................................................................................................................................ 33 3.1 Overview ................................................................................................................................... 33 3.2 Initial Considerations and influences from State of Art ......................................... 33 3.3 Requirements .......................................................................................................................... 34 3.4 User Interface and Visual Metaphors ............................................................................ 35 3.4.1 General exploration process .................................................................................... 37 3.4.2 Selecting initial film poster ....................................................................................... 37 3.4.3 Main exploration ........................................................................................................... 38 3.5 Technologies ........................................................................................................................... 42 3.5.1 Backend Architecture.................................................................................................. 42 3.5.2 Frontend Architecture ................................................................................................ 43 3.6 High Level Design / System Architecture .................................................................... 44 3.7 Semantic Attributes and User Model ............................................................................. 45 3.8 Conclusion ................................................................................................................................ 46 4 Implementation ............................................................................................................................