Human brains can be seen as knowledge processors in a distributed system. Each of them can achieve, conscious or not, a small part of a treatment too important to be done by one. These are also "hunter / gatherers" of knowledge. Provided that the number of contributors is large enough, the results are usually better quality than if they were the result of the activity of a single person, even if it is a domain expert. This type of activity is done via online games.
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ix | |
| Introduction |
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xiii | |
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Chapter 1 Biological Games |
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1 | (30) |
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2 | (3) |
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5 | (3) |
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8 | (3) |
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11 | (4) |
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15 | (3) |
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18 | (4) |
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22 | (3) |
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22 | (2) |
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24 | (1) |
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25 | (4) |
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1.8.1 Nightjar game/Nest game |
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26 | (2) |
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28 | (1) |
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29 | (2) |
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Chapter 2 Games with a Medical Purpose |
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31 | (16) |
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31 | (3) |
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34 | (1) |
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35 | (2) |
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2.4 Malaria Training Game |
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37 | (2) |
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39 | (3) |
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42 | (2) |
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2.7 Play to Cure: Genes in Space |
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44 | (1) |
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45 | (2) |
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Chapter 3 GWAPs for Natural Language Processing |
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47 | (26) |
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3.1 Why lexical resources? |
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47 | (1) |
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3.2 GWAPs for natural language processing |
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48 | (6) |
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3.2.1 The problem of lexical resource acquisition |
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49 | (1) |
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3.2.2 Lexical resources currently available |
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50 | (3) |
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3.2.3 Benefits of GWAPs in NLP |
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53 | (1) |
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54 | (3) |
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57 | (2) |
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59 | (2) |
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61 | (1) |
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62 | (2) |
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64 | (2) |
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66 | (2) |
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3.10 Other GWAPs dedicated to NLP |
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68 | (5) |
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3.10.1 Open Mind Word Expert |
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68 | (1) |
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69 | (1) |
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3.10.3 Categorilla/Categodzilla |
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69 | (1) |
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70 | (1) |
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70 | (1) |
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70 | (3) |
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Chapter 4 Unclassifiable GWAPs |
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73 | (18) |
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73 | (2) |
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75 | (1) |
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76 | (1) |
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77 | (3) |
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80 | (5) |
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4.5.1 ARTigo and ARTigo Taboo |
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81 | (2) |
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83 | (1) |
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83 | (2) |
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85 | (1) |
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4.7 Akinator, the genie of the Web |
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86 | (3) |
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89 | (2) |
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Chapter 5 The JeuxDeMots Project -- GWAPs and Words |
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91 | (28) |
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5.1 Building a lexical network |
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91 | (2) |
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5.2 JeuxDeMots: an association game |
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93 | (3) |
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5.3 PtiClic: an allocation game |
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96 | (2) |
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5.4 Totaki: a guessing game |
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98 | (1) |
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99 | (6) |
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100 | (2) |
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102 | (2) |
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104 | (1) |
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5.6 Multi-selection games |
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105 | (4) |
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5.7 From games to contributory systems |
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109 | (3) |
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5.8 Data collected and properties of the games presented |
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112 | (7) |
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5.8.1 Instructions/difficult relations |
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114 | (1) |
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5.8.2 Forcing, players typology and error rate |
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115 | (4) |
| Conclusion |
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119 | (8) |
| Bibliography |
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127 | (8) |
| Index |
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135 | |
Mathieu LAFOURCADE, LIRMM, Université Montpellier 2, France.
Alain JOUBERT, LIRMM, Université Montpellier 2, France.
Nathalie LE BRUN, Imagin@T, Fraance.
Lisainfo e-raamatute kohta