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HT MASH MAH AH SH MH Multi-model Adaptive Spatial Hypermedia Luis Francisco-Revilla Department of Computer Science Texas A&M University.

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Presentation on theme: "HT MASH MAH AH SH MH Multi-model Adaptive Spatial Hypermedia Luis Francisco-Revilla Department of Computer Science Texas A&M University."— Presentation transcript:

1 HT MASH MAH AH SH MH Multi-model Adaptive Spatial Hypermedia Luis Francisco-Revilla Department of Computer Science Texas A&M University

2 4 How effectively does the system function? 3 How was MASH instantiated? 5 What were the lessons learned? 1 What is Multi-model Adaptive Spatial Hypermedia? 2 What were the challenges in creating MASH?

3 1 Spatial Hypermedia Multi-model Adaptive Spatial Hypermedia Multi-model Adaptive Hypermedia Adaptive Hypermedia Map-based Hypermedia MASH

4 1 Hypermedia often provides a rigid presentation of the information Problem “Sometimes I want the link and sometimes I don’t” “I think these two objects might be related” HT MASH MAH AH SH MH

5 1 Adaptive Hypermedia Personalize presentations Adapt presentation to multiple aspects Hypermedia Multi model Adaptive Hypermedia Adaptive Hypermedia Task Model User Model Situation Model Risk Model HT MASH MAH AH SH MH

6 1 Multiple Independent Models Complexity and scalability Easier knowledge engineering Portability and reutilization Amortization of costs Privacy and distribution Control over personal models Not Very So-so Not So-so Very NotSo-soVery NotSo-soVery NotSo-soVery NotSo-soVery HT MASH MAH AH SH MH

7 1 Spatial Hypermedia There was a need to know the context Due to their heavy use, maps became the primary interface Hypermedia Spatial Hypermedia Map based Hypermedia Aquanet VKB HT MASH MAH AH SH MH

8 Spatial Hypermedia Objects are not restricted to represent documents (e.g. objects may represent chunks of information within a document) Navigational Hypertext Spatial Hypertext 1 HT MASH MAH AHMH SH

9 Spatial Hypermedia Navigational Hypertext Spatial Hypertext Objects are not restricted to represent documents (e.g. objects may represent chunks of information within a document) 1 HT MASH MAH AHMH SH

10 Spatial Hypermedia Navigational Hypertext Spatial Hypertext Objects are not restricted to represent documents (e.g. objects may represent chunks of information within a document) 1 SH HT MASH MAH AHMH

11 1 Spatial Hypermedia Users can interact with the information and see the effects of altering its structure Reflect “perceptually” vs. reflect “cognitively” HT MASH MAH AH SH MH

12 1 Spatial Hypermedia HT MASH MAH AH SH MH Communication is via perceivable structures Systems use spatial parsers in order to develop a shared understanding of these structures User Back-end Processes

13 1 Spatial Hypermedia In Web-based Spatial Hypermedia and Presentation Oriented Spatial Hypermedia, Readers and Authors are not the same person anymore HT MASH MAH AH SH MH

14 Spatial Hypermedia Multi-model Adaptive Spatial Hypermedia Multi-model Adaptive Hypermedia Adaptive Hypermedia Map-based Hypermedia 1 MASH

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16 Adaptation in Spatial Hypermedia Content Relational Spatial APPROACH Classification Suggestions Conflicts

17 Suggestions Object Model 1 Bold, Increase size Models provide suggestions of how to adapt the information presentation Classification Suggestions Conflicts 2 APPROACH

18 Suggestions Object Model 1 Bold, Increase size Models provide suggestions of how to adapt the information presentation Classification Suggestions Conflicts 2 APPROACH

19 Methods and Techniques Object Model 1 Emphasize Since Adaptive Hypermedia, high-level methods are translated to low-level techniques Classification Suggestions Conflicts 2 APPROACH

20 Methods and Techniques Object Model 1 Emphasize Emphasize = Bold, Increase size In Spatial Hypermedia the number of techniques increases Since Adaptive Hypermedia, high-level methods are translated to low-level techniques Classification Suggestions Conflicts 2 APPROACH

21 Methods and Techniques Object Model 1 Emphasize Emphasize = Change border color, Increase border width In Spatial Hypermedia the number of techniques increases Since Adaptive Hypermedia, high-level methods are translated to low-level techniques Classification Suggestions Conflicts 2 APPROACH Object

22 Methods and Techniques Object Model 1 Emphasize Emphasize = Change background color, Increase font size In Spatial Hypermedia the number of techniques increases Since Adaptive Hypermedia, high-level methods are translated to low-level techniques Classification Suggestions Conflicts 2 APPROACH Object

23 Methods and Techniques Object Model 1 Emphasize by 1.5; 0.80 confidence In Spatial Hypermedia the number of techniques increases Since Adaptive Hypermedia, high-level methods are translated to low-level techniques Suggestions specify the adaptation method, its strength and the model’s confidence in the suggestion Classification Suggestions Conflicts 2 APPROACH Emphasize = Change background color, Increase font size Object

24 Conflict Management Model 2 Prevent from viewing Object Model 1 Emphasize Conflicts occur when multiple adaptations cannot be simultaneously represented ? Classification Suggestions Conflicts 2 APPROACH

25 Conflict Management Model 2 Prevent from viewing Object Model 1 Emphasize ? Managing conflicts is more than resolving conflicts Manage conflicts: Prevention Detection Resolution Classification Suggestions Conflicts Conflicts occur when multiple adaptations cannot be simultaneously represented 2 APPROACH

26 Conflict Prevention Augment medium expressiveness Dynamically map high-level methods low-level techniques Embrace ambiguity Model 1 Emphasize Model 2 Emphasize  Increase font size De-emphasize  Fade out De-emphasize Classification Suggestions Conflicts 2 APPROACH

27 Conflict Detection Conflict propagation Scope of conflicts Spatial parser Suggestion 1 Suggestion 2 It does not look like a list anymore! Conflicts can propagate in many directions Classification Suggestions Conflicts Since the communication is via perceptible structures, when the structures break the communication breaks 2 APPROACH Suggestion 1 Suggestion 2

28 Conflict Resolution Merge suggestions Strategies: Weighted average Suggestion strength Suggestion confidence Model confidence Heuristic best Object Model 1: emphasize Model 2: de-emphasize Object average suggestions Classification Suggestions Conflicts 2 APPROACH

29 Determine mapping from adaptation methods to techniques Balancing author and reader control Specify mapping and resolution strategies Conflict Resolution emphasize Object emphasize Object emphasize Classification Suggestions Conflicts 2 APPROACH

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31 3 SYSTEM WARP Multi-model Adaptive Spatial Hypermedia Executes in a Web-browser Novel features Transclusion links Personal readings Annotations Behaviors WARP Behaviors Process

32 3 SYSTEM Demo 1 WARP Behaviors Process Relationships: Explicit, Implicit, Transclusion Behaviors Online News Collections Commercial Web-page Transclusion, Import and Export

33 3 SYSTEM Behaviors User actions and system adaptations can affect existing spatial structures Spatial parser identifies structures Behaviors can preserve spatial relationships WARP Behaviors Process

34 3 SYSTEM Adaptation Process (1) Objects prior to adaptation Platform Parser Analyzer Transformer WARP Behaviors Process

35 3 SYSTEM Adaptation Process (2) Inference of implicit structures Platform Parser Analyzer Transformer M1M1 M2M2 MnMn Models WARP Behaviors Process

36 3 SYSTEM Adaptation Process (3) Context inference and conflict prevention Platform Parser Analyzer Transformer M1M1 M2M2 MnMn Models WARP Behaviors Process

37 3 SYSTEM Adaptation Process (4) Suggestion of adaptations Platform Parser Analyzer Transformer M1M1 M2M2 MnMn Models WARP Behaviors Process

38 3 SYSTEM Adaptation Process (5) Transformation and adaptations Platform Parser Analyzer Transformer M1M1 M2M2 MnMn Models WARP Behaviors Process

39 3 SYSTEM Adaptation Process (6) Extended conflict detection Platform Parser Analyzer Transformer M1M1 M2M2 MnMn Models Conflict? WARP Behaviors Process

40 3 SYSTEM Adaptation Process (7) Alternative creation Platform Parser Analyzer Transformer M1M1 M2M2 MnMn Models Alternatives WARP Behaviors Process

41 3 SYSTEM Adaptation Process (8) Evaluation of alternatives Platform Parser Analyzer Transformer M1M1 M2M2 MnMn Models OK? WARP Behaviors Process

42 3 SYSTEM Adaptation Process (9) Final adaptation Platform Parser Analyzer Transformer WARP Behaviors Process

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44 Objectives Comparative study Non-adaptive spatial hypermedia Multi-model adaptive spatial hypermedia Investigate the effects of adaptation in the process of reading spatial hypermedia Usability of the system 4 EVALUATION Experiment Qualitative Quantitative 3 2 1

45 Population 16 participants years old From Texas A&M University and Bryan/College Station community Varying degrees of expertise (8 beginner, 8 advanced) Experiment Qualitative Quantitative 4 EVALUATION

46 Task Web designers for a non-profit organization Must author a Web page using a text editor in 90 minutes Requirements and evaluation metrics for the Web page Spatial hypertext about HTML as information support Experiment Qualitative Quantitative 4 EVALUATION

47 Evaluation Procedure 2:30 hours Interview10 minutes Completing the questionnaire about use of the system10 minutes Authoring Web page90 minutes Completing the HTML and XHTML questionnaire20 minutes Completing the computer and Web expertise questionnaire5 minutes Training in software tools (WARP and authoring environment)15 minutes ActivityTime Experiment Qualitative Quantitative 4 EVALUATION

48 Initial Interface (not adapted) Experiment Qualitative Quantitative 4 EVALUATION

49 Demo 2 Experiment Qualitative Quantitative Adaptation of the experiment’s interface 4 EVALUATION

50 User Model Initialization Experiment Qualitative Quantitative 4 EVALUATION

51 Initial interface (adapted for beginner) Experiment Qualitative Quantitative 4 EVALUATION

52 Initial Interface (adapted for advanced) Experiment Qualitative Quantitative 4 EVALUATION

53 Document Design Content Kennedy and Musciano “HTML & XHTML: The Definitive Guide” O’Reilley’s, 2002 Layout Encapsulate topics and subtopics Visually reflect the structure of the information Limited dynamic behaviors Adaptive behaviors Multiple visual cues – size, font size, glow, alpha blur, zooming Experiment Qualitative Quantitative 4 EVALUATION

54 Qualitative Results Gathered from observations, questionnaires, interviews and comments Emergent reading strategies Changes in reading behavior Experiment Qualitative Results Quantitative Spatial layouts Moving and rearranging Collections and bookmarks Informed link traversals Adaptation and reading 4 EVALUATION

55 Spatial Layouts Easy navigation of large information spaces Effective concept encapsulation Reflect information structure “I really like that I can see all of the chapters” Experiment Qualitative Results Quantitative 4 EVALUATION

56 Moving and Rearranging …to indicate what is being read or what has been read..to indicate “what is more important” …in order to “see both and compare” …“for reference” Experiment Qualitative Results Quantitative 4 EVALUATION

57 Informed Link Traversal Informed link traversal Browsing before committing to maximizing collections “You are not clicking on a bunch of links that may or may not have what you are looking for” Experiment Qualitative Results Quantitative 4 EVALUATION

58 Collections and Bookmarks Maximizing sub-collections to bookmark sections Minimizing collections as “I’m done with that!” Experiment Qualitative Results Quantitative 4 EVALUATION

59 Adaptation and Reading Adaptation changed the way people read Implementation guidelines: Using multiple visual cues Allow readers to maintain control of the process “What red glow?” Experiment Qualitative Results Quantitative 4 EVALUATION

60 Quantitative Results Assessments of the quality of the Web pages in regards to: Content Presentation Overall Scores computed according to pre-established metrics (provided to the users) Experiment Qualitative Results Quantitative Results 4 EVALUATION

61 ANOVA Significantly better for the Adaptive case Advanced users generated significantly better Web pages Possible interaction Overallp = Contentp = Presentationp = Non-adaptive vs. Adaptive Overallp < Contentp < Presentationp < Novice vs. Advanced Overallp = Contentp = Presentationp = Expertise-Adaptation Interaction Experiment Qualitative Results Quantitative Results 4 EVALUATION

62 Expertise and Overall Scores Expertise vs. overall scores in the non-adaptive case Expertise = HTML knowledge * (1 + Previous knowledge) Experiment Qualitative Results Quantitative Results 4 EVALUATION

63 Expertise and Overall Scores Experiment Qualitative Results Quantitative Results Expertise vs. overall scores in the adaptive case 4 EVALUATION Expertise = HTML knowledge * (1 + Previous knowledge)

64 Expertise and Overall Scores Some clustering No significant correlation between expertise and score Experiment Qualitative Results Quantitative Results 4 EVALUATION Expertise = HTML knowledge * (1 + Previous knowledge)

65 Expertise and Overall Scores Experiment Qualitative Results Quantitative Results 4 EVALUATION Some clustering No significant correlation between expertise and score Expertise = HTML knowledge * (1 + Previous knowledge)

66 Experiment Qualitative Results Quantitative Results Expertise and Overall Scores 4 EVALUATION Some clustering No significant correlation between expertise and score Expertise = HTML knowledge * (1 + Previous knowledge)

67 Experiment Qualitative Results Quantitative Results Expertise and Overall Scores 4 EVALUATION Some clustering No significant correlation between expertise and score Expertise = HTML knowledge * (1 + Previous knowledge)

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69 Lessons learned Future work 5 CONCLUSIONS Conclusions Spatial Hypermedia supports the navigation of very large information spaces Adaptive Spatial Hypermedia enhances the users’ ability to find the right information Adaptation in Spatial Hypermedia is more elaborate than in Navigational Hypermedia Adaptation affects the process of reading in Spatial Hypermedia The use multiple independent models in the adaptation process is feasible and facilitates aspects such as authoring, reuse and distribution

70 Lessons learned Future work Future Work CSCW implications Mixed media and dynamic presentations Interface for back-end systems: Software engineering Interface for digital libraries and search engines 5 CONCLUSIONS Use machine learning in order to learn how to adjust automatically the adaptation parameters

71 Lessons learned Future work Broader Interests 5 CONCLUSIONS Adaptive visualization for content data analysis Accessibility issues Cross-cultural communication issues 3 1 2

72 Questions?


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