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Visualizing Hierarchical Knowledge As Insightful Islands Bin Yang Memory Island : Visualizing Hierarchical Knowledge as Insightful Islands Bin Yang To cite this version: Bin Yang. Memory Island : Visualizing Hierarchical Knowledge as Insightful Islands. Information Retrieval [cs.IR]. Université Pierre et Marie Curie - Paris VI, 2015. English. NNT : 2015PA066137. tel-01241135 HAL Id: tel-01241135 https://tel.archives-ouvertes.fr/tel-01241135 Submitted on 10 Dec 2015 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Université Pierre et Marie Curie École doctorale Informatique, Télécommunications et Électronique (Paris) (ED130) Lip6 ACASA Group MEMORY ISLAND: VISUALIZING HIERARCHICAL KNOWLEDGE AS INSIGHTFUL ISLANDS Présentée Par Bin Yang Thèse de doctorat d’Informatique Dirigée par Monsieur le professeur Jean-Gabriel Ganascia Présentée et soutenue publiquement le 08 Juin 2015 Devant un jury composé de: Monsieur Dragicevic, Pierre, Chargé de Recherche, Examinateur Professeur Ganascia, Jean-Gabriel, Professeur, Directeur de these Professeur Kuntz-Cosperec, Pascale, Professeur, Rapporteur Professeur Labat, Jean-Marc, Professeur, Examinateur Monsieur Lecolinet, Eric, Maître de Conférences, Examinateur Professeur Venturini,Gilles, Professeur, Rapporteur This thesis is dedicated to my parent and my wife Xiang. Thank you for the wealth of love. i ii ABSTRACT This thesis is devoted to the study of an original cartographic visualization approach named Memory Island. We discuss how hierarchical knowledge can be meaningfully mapped and visualized as an insightful island. Our technique is inspired by the "loci" (plural of Latin "locus" for places or locations) method of the ancient "Art of Memory" technique. A well-designed map in mind can make sense of knowledge, which leads to the accomplishment of one's information seeking tasks, and helps to extend one's knowledge. To this end, Memory Island technique consists of associating each entity of knowledge to a designated area on a created virtual island. With the geographic visual metaphors we define, Memory Island can present phenomena found in knowledge, which is often difficult to understand. In this thesis, we discuss how we design our visualization technique to make it achieve the great features of visualization: automatically generate a truthful, functional, beautiful, insightful, and enlightening island with its technical details. In order to make Memory Island more convenient for its users, we present our "overview+detail" interface, to support them with visual exploration and knowledge analysis. We also demonstrate how to create knowledge maps using Memory Island technique, by giving some example on different datasets of Digital Humanities (Project OBVIL), e-books (Project LOCUPLETO) and other domains. Then, we propose our validation and evaluation protocols with two preliminary user experiments. The results from these studies indicate that the use of Memory Island provides advantages for non-experienced users tackling realistic browsing, helps them improve their performances in knowledge navigation and memorization tasks, and that most of them choose to use it for navigation and knowledge discovery. We end up by concluding our researches and listing some perspectives and future works that can be based on our Memory Island technique. iii iv TITRE EN FRANÇAISE « ILES DE MEMOIRES: UNE NOUVELLE APPROCHE POUR LA VISUALISATION INTUITIVE DES CONNAISSANCES HIERARCHIQUES» RE SUME Dans cette thèse nous étudions une nouvelle approche de visualisation cartographique appelée « îles de mémoires ». Le terme « îles de mémoires » a été inspiré par la méthode des «loci» (pluriel de « locus » en latin qui signifie « endroit » ou « lieu») de l’ancien « Art de la mémoire». Une carte bien représentée dans l’esprit peut donner un sens à la connaissance, ce qui améliore une de recherche d'information (une recherche intuitive), et contribue à enrichir les connaissances issues de cette carte. Pour cela, la technique « îles de mémoires » consiste à associer chaque entité de connaissance à un endroit désigné sur une île virtuelle. Grâce aux les métaphores géographiques que nous avons définies, une représentation en « îles de mémoires » peut inférer des phénomènes souvent difficile à identifier et comprendre dans la connaissance. Dans une première partie, nous détaillons notre approche de visualisation d’une hiérarchie de connaissances en île de mémoire. Nous présentons les algorithmes que nous avons définis pour générer automatiquement une belle carte réaliste, fonctionnelle, intuitive et inspirante. Nous présentons aussi l’interface de visualisation "overview+detail" qui permet de naviguer dans les îles de mémoire. Dans une deuxième partie, nous détaillons les expérimentations réalisées avec notre outil dans le cadre du projet LOCUPLETO et des exemples issus du domaine des humanités numériques (Projet OBVIL, InPhO, etc.). Les résultats obtenus avec notre approche de visualisation sont prometteuses. En effet, les résultats démontrent que la navigation est intuitive et est capable d’augmenter la mémorisation des connaissances chez les utilisateurs de l’outil. Nous concluions notre thèse par le bilan des travaux menées et nous proposons un ensemble de travaux futurs basé sur notre approche de visualisation « îles de mémoires ». v ACKNOWLEDGEMENTS This work is supported by the French National Research Project (investissement d'avenir) LOCUPLETO. This work has been possible only because of the French National Research Project (investissement d'avenir) LOCUPLETO. I thank all the participants of the Project LOCUPLETO and the participants of our user studies. Professor Jean-Gabriel Ganascia has been the ideal thesis supervisor. His sage advice, insightful criticisms, and patient encouragement aided the working and writing of this thesis in innumerable ways. I want to thank Raluca Tocmag, Suradej Panich, Marie Laxenaire, Soroosh Nalchigar and Fabio Pardo for their interns and supports for the evaluation experiments. I would like to thank for Professor Gilles Venturini and Professor Pascale Kuntz-Cosperec for their interests they have shown with this thesis, and their agreement to examine this thesis in detail as reviewers. I also appreciate Professor Jean-Marc Labat, Dr. Pierre Dragicevic and Dr. Eric Lecolinet for accepting to examine this work and it’s my pleasure that they can participate in my thesis committee. I also want to give my specific thanks to Dr. Jean-Daniel Fekete, even unfortunately, he cannot by my thesis committee as he is on sabbatical year on the USA. He suggest me to invite Dr. Pierre Dragicevic who is an ideal thesis committee. I have had the good fortune to be able to present my research in several conferences and workshops, and would like to thank everyone who made this possible, including anonymous reviewers who offered valuable input. I would like to thank also the Association EGC, and AFIHM (L'Association Francophone d'Interaction Homme-Machine), who have organized the workshops on InfoVis, give me a chance to discuss our idea with others. I thank the Cost Action TD1210, who bring me the opportunities and support me to present my research in many places in Europe. I also thanks to the members of Labex OBVIL, who give me the rights to apply Memory Island on their dataset and the encouragements from them. I also thank the editors, Aida Slavic and Almila Akdag Salah of the International UDC Seminar 2013 proceedings for valuable comments and suggestions for improving our works. I would like to thank for Professor Colin Allen of Indiana University Bloomington for his comments and helps when we work on his InPhO ontology. I would like also thanks the Research Scientist Michaël AUPETIT of Qatar Computing Research Institute, he give me some reference on how to design a visualization tools. I appreciate the encouragement and useful suggestions of Professor Andre Skupin of San Diego State University, Professor Charles van den Heuvel of University of Amsterdam and Xia Lin of Drexel University for the valuable discussion on Memory Island. I want to give my specific thanks to the people in ACASA Team at Lip6: Christophe Jouis, Gauvain Bourgne, Mihnea Tufis, Alexandre Bazin, Mohamed Amine Boukhaled, Suzanne vii Mpouli Njanga Seh, Fiona Berreby, Alaa Abi Haidar Zied Sellami and Francesca Frontini. I have passed wonderful three years with all of you for both my research and my stays in Paris. Thank you to Kayla Friedman and Malcolm Morgan of the Centre for Sustainable Development, University of Cambridge, UK and the IFD department of University Pierre and Marie Curie for producing their Microsoft Word thesis templates used to produce this document. In the end, I would like to give my specific thanks to Marco Quaggiotto, Martin Rosvall and Andrea Scharnhorst who allow me to reproduce your images in my thesis. viii Memory Island: Visualizing Hierarchical Knowledge as Insightful Islands Bin Yang‐ June 2015 CONTENTS PART I. BACKGROUND AND LITERATURE REVIEW ....................................................................... 1 CHAPTER 1 GENERAL INTRODUCTION .....................................................................................................................
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