1. David Brokenshire, Jurika Shakya, and Vive Kumar
Providing Information for Mixed Initiative Interaction via Interoperable User Modelling
David Brokenshire, Jurika Shakya, and Vive Kumar
This work supported by NSERC (LORNet) and SSHRC (LearningKit)

2. Ontology

3. + communication

4. interoperability

5. Reuse of
Data & Systems

7. adaptor

13. Who Is this?

14. Agent

15. general

16. Who cares?

17. What for?

18. User Modelling

19. Research Disease

20. Solitary

21. They can’t talk

22. They should

23. getting knowledge

24. hard

25. Cold start

26. need

27. knowledge

28. now

29. help

30. time

31. bother

32. I care

33. user modelling

36. should you care?

37. mixed initiative

38. uses

39. user modelling

41. but still

42. doesn’t

43. share

44. example

45. bother

46. fleming, cohen, et al

47. agents

48. models

49. bother

50. users

51. but…

52. my agents

53. bother

54. your users

55. without you knowing

57. so let’s share

58. enough example (for now)

59. how does it work?

62. models

63. communicate

64. via

65. agents

66. using

67. ontologies

68. proposal

69. Community of agents

70. Discoverable online

71. Using FIPA/JADE

72. provide access

73. user models & data

74. agent architecture

75. two main parts

76. user model agent

77. data to information agent (adaptor)

78. plus ontology/extender agent

79. now some detail

80. Data Source

81. has information you want

82. raw, unprocessed

83. no idea you want it

84. Data to Information Agent

85. an adaptor

86. knows how to access a Data Source

87. but converts to ontology

88. makes data available

89. User Model Agent

90. connects user model to the world

91. also converts to ontology

92. but can answer more questions

93. Ontology Agent

94. provides mappings between ontologies

95. key to interoperability

96. scenario

97. connecting MI-Edna and Helper’s Assistant

98. MI-Edna

99. model of SRL

100. with ontology

101. Helper’s Assistant

102. needs context information

104. Create User Model Agent for MI-Edna

105. How?

106. Take default agent behaviour

107. extend

108. UMA takes ontology based requests

109. Makes calls to MI-Edna UM

110. Returns ontology results

112. Create User Model Agent for Helper’s Assistant

113. Same process, but

114. no existing ontology!

115. Two choices

116. Make a new ontology

117. Use MI-Edna’s ontology

118. Assume same ontology

119. Helper’s Assistant User Model Agent must

120. connect to Helper’s Assistant and

121. Convert MI-Edna ontology to calls

123. But what if HA has its own ontology?

124. Build user model agent for Helper’s Assistant ontology

125. But now…

127. No Common Ontology!

128. Need mapping!
(This is key!)

129. Ontology Agent

130. common ontology or mapping allows interoperability

131. agnostic

132. rapidly developing

133. somebody else’s problem

134. that’s the basics…

135. to summarize

136. Ontology

137. + communication

138. interoperability

139. Reuse of
Data & Systems

140. propose

141. models

142. communicate

143. via

144. Community of agents

145. Discoverable online

146. Using FIPA/JADE

147. Where are we now?

148. Prototype implemented

149. Connects to SPARC ePortfolios

150. What does the future hold?

151. problems to solve

152. privacy

153. security

154. Connecting our systems

155. SPARC ePortfolios

156. MI-Edna

157. gStudy + gLiza

158. MI-Games

159. Helper’s Assistant

160. Questions?