System for identifying data relationships

• US 20060085370A1
• Filed: 12/13/2002
• Published: 04/20/2006
• Est. Priority Date: 12/14/2001
• Status: Abandoned Application

• Current Assignee: Kate Armstrong, Robert Groat
• Original Assignee: Kate Armstrong, Robert Groat
• Inventors: Armstrong, Kate, Groat, Robert
• Application Number:
  US10/476,161
• Publication Number:
  US 20060085370A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/9024 Graphs; Linked lists G06F16/9027 takes precedence
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes

Abstract

A method for identifying data relationships comprising the steps of providing source data, reducing the data into canonical data, so that the canonical data is capable of being used in an inferential web that shows a user connections between at least two entities. Preferably, the inferential web is displayed to the user and may be stored on data storage medium. The method for identifying data relationship may be implemented by a computer.

Claims

1. A method for identifying data relationships comprising the steps of:

(a) providing source data; and

(b) reducing said data into canonical data, said canonical data being capable of being used in an inferential web that shows a user connections between at least two entities.

2. The method of claim 1, wherein said method further comprises the step of displaying said canonical data to a user on a visual display apparatus.

3. The method of claim 1, wherein said method further comprises the step of storing said canonical data on a data storage medium.

4. The method of claim 1, wherein said canonical data comprises transactional canonical data.

5. The method of claim 4, wherein each of said transactional canonical data comprises no more than 3 transactional canonical data elements.

6. The method of claim 4, wherein said canonical data comprises relationship canonical data.

7. The method of claim 1, wherein said canonical data comprises relationship canonical data.

8. The method of claim 1, wherein said method is implemented in a computer system.

9. A method for structuring data comprising the steps of:

(a) providing a plurality of canonical data; and

(b) organizing said canonical data into an inferential web comprising a plurality of nodes and at least one vertex connecting at least two connected nodes of said plurality of nodes, wherein said inferential web shows a user connections between a plurality of entities.

10. The method of claim 9, wherein said method further comprises the step of displaying said inferential web to a user on a visual display apparatus.

11. The method of claim 9, wherein said method further comprises the step of storing said inferential web on a data storage medium.

12. The method of claim 9, wherein said canonical data is structured into said inferential web based on a plurality of connections present in said plurality of canonical data.

13. The method of claim 9, wherein said method further comprises the step of assigning weight to said at least one vertex.

14. The method of claim 9, wherein said method further comprises the step of assigning a direction to said at least one vertex.

15. The method of claim 9, wherein said canonical data comprises transactional canonical data.

16. The method of claim 15, wherein each of said transactional canonical data comprises no more than 3 transactional canonical data elements.

17. The method of claim 15, wherein said canonical data comprises relationship canonical data.

18. The method of claim 9, wherein said canonical data comprises relationship canonical data.

19. The method of claim 9, wherein said method is implemented in a computer system.

20. A data structure comprising:

canonical data, said canonical data being organized into a plurality of nodes and at least one vertex connecting at least two connected nodes of said plurality of nodes, wherein said data structure comprises an inferential web that shows a user connections between at least two entities.

21. The data structure of claim 20, wherein said inferential web is displayed to a user on a visual display apparatus.

22. The data structure of claim 20, wherein said inferential web is stored in a data storage medium.

23. The data structure of claim 20, wherein at least some of said nodes are secure nodes.

24. The data structure of claim 20, wherein said data structure is collapsible.

25. The data structure of claim 20, wherein said data structure is expandable.

26. The data structure of claim 20, wherein said data structure is combinable.

27. The data structure of claim 20, wherein said data structure is extractable.

28. The data structure of claim 20, wherein said at least two connected nodes comprises a plurality of connected nodes.

29. The data structure of claim 20, wherein said at least one vertex comprises a plurality of vertices.

30. The data structure of claim 29, wherein at least some of said plurality of vertices are weighted vertices.

31. The data structure of claim 30, wherein at least some of said weighted vertices are dynamically weighted vertices.

32. The data structure of claim 29, wherein at least some of said plurality of vertices are directional vertices.

33. The data structure of claim 20, wherein said canonical data comprises transactional canonical data.

34. The data structure of claim 33, wherein each of said transactional canonical data comprises no more than 3 transactional canonical data elements.

35. The data structure of claim 33, wherein said canonical data comprises relationship canonical data.

36. The data structure of claim 20, wherein said canonical data comprises relationship canonical data.

37. The data structure of claim 20, wherein said data structure is located in a computer system.

38. The data structure of claim 20, wherein said data structure is located on a data storage medium.

39. A method of modifying a data structure comprising the steps of:

(a) providing an inferential web comprising canonical data, said canonical data being organized into a plurality of nodes and at least one vertex connecting at least two connected nodes of said nodes, wherein said data structure comprises an inferential web that shows a user connections between at least two entities; and

(b) modifying said inferential web to form a modified inferential web.

40. The method of claim 39, wherein said method further comprises the step of displaying said modified inferential web to a user on a visual display apparatus.

41. The method of claim 39, wherein said method further comprises the step of storing said modified inferential web on a data storage medium.

42. The method of claim 39, wherein step (b) comprises assigning a weight to said at least one vertex.

43. The method of claim 39, wherein step (b) comprises modifying a weight of said at least one vertex.

44. The method of claim 39, wherein step (b) comprises assigning a direction to said at least one vertex.

45. The method of claim 39, wherein step (b) comprises modifying a direction of said at least one vertex.

46. The method of claim 39, wherein step (b) comprises collapsing at least a portion of said inferential web.

47. The method of claim 39, wherein step (b) comprises expanding at least a portion of said inferential web.

48. The method of claim 39, wherein step (b) comprises combining at least a portion of said inferential web with a second inferential web.

49. The method of claim 39, wherein step (b) comprises extracting at least a portion of said inferential web,

50. The method of claim 39, wherein at least some of said nodes are secure nodes.

51. The method of claim 39, wherein said at least two connected nodes comprises a plurality of connected nodes.

52. The method of claim 39, wherein said at least one vertex comprises a plurality of vertices.

53. The method of claim 39, wherein said inferential web is modified due to said inferential web being queried by said user.

54. The method of claim 39, wherein said canonical data comprises transactional canonical data.

55. The method of claim 54, wherein each of said transactional canonical data comprises no more than 3 transactional canonical data elements.

56. The method of claim 54, wherein said canonical data comprises relationship canonical data.

57. The method of claim 39, wherein said canonical data comprises relationship canonical data.

58. The method of claim 39, wherein said method is implemented in a computer system.

59. A method of alerting a user if a data structure is modified comprising the steps of:

(a) providing an inferential web comprising canonical data, said canonical data being organized into a plurality of nodes and at least one vertex connecting at least two connected nodes of said nodes, wherein said data structure comprises an inferential web that shows a user connections between at least two entities; and

(b) alerting the user if said inferential web is modified to form a modified inferential web.

60. The method of claim 59, wherein said inferential web is modified by a weight being assigned to said at least one vertex.

61. The method of claim 59, wherein said inferential web is modified by a weight of said at least one vertex being modified.

62. The method of claim 59, wherein said inferential web is modified by a direction being assigned to said at least one vertex.

63. The method of claim 59, wherein said inferential web is modified by a direction of said at least one vertex being modified.

64. The method of claim 59, wherein said inferential web is modified by collapsing at least a portion of said inferential web.

65. The method of claim 59, wherein said inferential web is modified by expanding at least a portion of said inferential web.

66. The method of claim 59, wherein said inferential web is modified by combining at least a portion of said inferential web with a second inferential web.

67. The method of claim 59, wherein said inferential web is modified by extracting at least a portion of said inferential web,

68. The method of claim 59, wherein at least some of said nodes are secure nodes.

69. The method of claim 59, wherein said at least two connected nodes comprises a plurality of connected nodes.

70. The method of claim 59, wherein said at least one vertex comprises a plurality of vertices.

71. The method of claim 59, wherein said inferential web is modified due to said inferential web being queried by said user.

72. The method of claim 59, wherein said user is alerted by a visible alert.

73. The method of claim 59, wherein said user is alerted by an audible alert.

74. The method of claim 59, wherein said canonical data comprises transactional canonical data.

75. The method of claim 74, wherein each of said transactional canonical data comprises no more than 3 transactional canonical data elements.

76. The method of claim 74, wherein said canonical data comprises relationship canonical data.

77. The method of claim 59, wherein said canonical data comprises relationship canonical data.

78. The method of claim 59, wherein said method is implemented in a computer system.

79. A computer system implementing a method for identifying data relationships, wherein said method comprises the steps of:

(a) providing source data; and

(b) reducing said data into canonical data, said canonical data being capable of being used in an inferential web that shows a user connections between at least two entities.

80. The computer system of claim 79, wherein said method further comprises the step of displaying said canonical data to a user on a visual display apparatus.

81. The computer system of claim 79, wherein said method further comprises the step of storing said canonical data on a data storage medium.

82. The computer system of claim 79, wherein said canonical data comprises transactional canonical data.

83. The computer system of claim 82, wherein each of said transactional canonical data comprises no more than 3 transactional canonical data elements.

84. The computer system of claim 82, wherein said canonical data comprises relationship canonical data.

85. The computer system of claim 79, wherein said canonical data comprises relationship canonical data.

86. The computer system of claim 79, wherein said method is implemented in a computer system.

87. A computer system implementing a method for structuring data, wherein said method comprises the steps of:

(a) providing a plurality of canonical data; and

(b) organizing said canonical data into an inferential web comprising a plurality of nodes and at least one vertex connecting at least two connected nodes of said plurality of nodes, wherein said inferential web shows a user connections between a plurality of entities.

88. The computer system of claim 87, wherein said method further comprises the step of displaying said inferential web to a user on a visual display apparatus.

89. The computer system of claim 87, wherein said method further comprises the step of storing said inferential web on a data storage medium.

90. The computer system of claim 87, wherein said canonical data is structured into said inferential web based on a plurality of connections present in said plurality of canonical data.

91. The computer system of claim 87, wherein said method further comprises the step of assigning weight to said at least one vertex.

92. The computer system of claim 87, wherein said method further comprises the step of assigning a direction to said at least one vertex.

93. The computer system of claim 87, wherein said canonical data comprises transactional canonical data.

94. The computer system of claim 93, wherein each of said transactional canonical data comprises no more than 3 transactional canonical data elements.

95. The computer system of claim 93, wherein said canonical data comprises relationship canonical data.

96. The computer system of claim 87, wherein said canonical data comprises relationship canonical data.

97. The computer system of claim 87, wherein said method is implemented in a computer system.

98. A computer system implementing a method of modifying a data structure, wherein said method comprises the steps of:

(a) providing an inferential web comprising canonical data, said canonical data being organized into a plurality of nodes and at least one vertex connecting at least two connected nodes of said nodes, wherein said data structure comprises an inferential web that shows a user connections between at least two entities; and

(b) modifying said inferential web to form a modified inferential web.

99. The computer system of claim 98, wherein said method further comprises the step of displaying said modified inferential web to a user on a visual display apparatus.

100. The computer system of claim 98, wherein said method further comprises the step of storing said modified inferential web on a data storage medium.

101. The computer system of claim 98, wherein step (b) comprises assigning a weight to said at least one vertex.

102. The computer system of claim 98, wherein step (b) comprises modifying a weight of said at least one vertex.

103. The computer system of claim 98, wherein step (b) comprises assigning a direction to said at least one vertex.

104. The computer system of claim 98, wherein step (b) comprises modifying a direction of said at least one vertex.

105. The computer system of claim 98, wherein step (b) comprises collapsing at least a portion of said inferential web.

106. The computer system of claim 98, wherein step (b) comprises expanding at least a portion of said inferential web.

107. The computer system of claim 98, wherein step (b) comprises combining at least a portion of said inferential web with a second inferential web.

108. The computer system of claim 98, wherein step (b) comprises extracting at least a portion of said inferential web,

109. The computer system of claim 98, wherein at least some of said nodes are secure nodes.

110. The computer system of claim 98, wherein said at least two connected nodes comprises a plurality of connected nodes.

111. The computer system of claim 98, wherein said at least one vertex comprises a plurality of vertices.

112. The computer system of claim 98, wherein said inferential web is modified due to said inferential web being queried by said user.

113. The computer system of claim 98, wherein said canonical data comprises transactional canonical data.

114. The computer system of claim 113, wherein each of said transactional canonical data comprises no more than 3 transactional canonical data elements.

115. The computer system of claim 113, wherein said canonical data comprises relationship canonical data.

116. The computer system of claim 98, wherein said canonical data comprises relationship canonical data.

117. The computer system of claim 98, wherein said method is implemented in a computer system.

118. A computer system implementing a method of alerting a user if a data structure is modified, wherein said method comprises the steps of:

(a) providing an inferential web comprising canonical data, said canonical data being organized into a plurality of nodes and at least one vertex connecting at least two connected nodes of said nodes, wherein said data structure comprises an inferential web that shows a user connections between at least two entities; and

(b) alerting the user if said inferential web is modified to form a modified inferential web.

119. The computer system of claim 118, wherein said inferential web is modified by a weight being assigned to said at least one vertex.

120. The computer system of claim 118, wherein said inferential web is modified by a weight of said at least one vertex being modified.

121. The computer system of claim 118, wherein said inferential web is modified by a direction being assigned to said at least one vertex.

122. The computer system of claim 118, wherein said inferential web is modified by a direction of said at least one vertex being modified.

123. The computer system of claim 118, wherein said inferential web is modified by collapsing at least a portion of said inferential web.

124. The computer system of claim 118, wherein said inferential web is modified by expanding at least a portion of said inferential web.

125. The computer system of claim 118, wherein said inferential web is modified by combining at least a portion of said inferential web with a second inferential web.

126. The computer system of claim 118, wherein said inferential web is modified by extracting at least a portion of said inferential web,

127. The computer system of claim 118, wherein at least some of said nodes are secure nodes.

128. The computer system of claim 118, wherein said at least two connected nodes comprises a plurality of connected nodes.

129. The computer system of claim 118, wherein said at least one vertex comprises a plurality of vertices.

130. The computer system of claim 118, wherein said inferential web is modified due to said inferential web being queried by said user.

131. The computer system of claim 118, wherein said user is alerted by a visible alert.

132. The computer system of claim 118, wherein said user is alerted by an audible alert.

133. The computer system of claim 118, wherein said canonical data comprises transactional canonical data.

134. The computer system of claim 133, wherein each of said transactional canonical data comprises no more than 3 transactional canonical data elements.

135. The computer system of claim 133, wherein said canonical data comprises relationship canonical data.

136. The computer system of claim 118, wherein said canonical data comprises relationship canonical data.

137. The computer system of claim 118, wherein said method is implemented in a computer system.

193. The machine-readable medium of claim 133, wherein each of said transactional canonical data comprises no more than 3 transactional canonical data elements.

194. The machine-readable medium of claim 133, wherein said canonical data comprises relationship canonical data.

138. A machine-readable medium storing instructions that, if executed by a computer system, causes the computer system to perform method for identifying data relationships comprising the steps of:

(a) providing source data; and

(b) reducing said data into canonical data, said canonical data being capable of being used in an inferential web that shows a user connections between at least two entities.

139. The machine-readable medium of claim 138, wherein said method further comprises the step of displaying said canonical data to a user on a visual display apparatus.

140. The machine-readable medium of claim 138, wherein said method further comprises the step of storing said canonical data on a data storage medium.

141. The machine-readable medium of claim 138, wherein said canonical data comprises transactional canonical data.

142. The machine-readable medium of claim 141, wherein each of said transactional canonical data comprises no more than 3 transactional canonical data elements.

143. The machine-readable medium of claim 141, wherein said canonical data comprises relationship canonical data.

144. The machine-readable medium of claim 138, wherein said canonical data comprises relationship canonical data.

145. The machine-readable medium of claim 138, wherein said method is implemented in a computer system.

146. A machine-readable medium storing instructions that, if executed by a computer system, causes the computer system to perform a method for structuring data comprising the steps of:

(a) providing a plurality of canonical data; and

(b) organizing said canonical data into an inferential web comprising a plurality of nodes and at least one vertex connecting at least two connected nodes of said plurality of nodes, wherein said inferential web shows a user connections between a plurality of entities.

147. The machine-readable medium of claim 146, wherein said method further comprises the step of displaying said inferential web to a user on a visual display apparatus.

148. The machine-readable medium of claim 146, wherein said method further comprises the step of storing said inferential web on a data storage medium.

149. The machine-readable medium of claim 146, wherein said canonical data is structured into said inferential web based on a plurality of connections present in said plurality of canonical data.

150. The machine-readable medium of claim 146, wherein said method further comprises the step of assigning weight to said at least one vertex.

151. The machine-readable medium of claim 146, wherein said method further comprises the step of assigning a direction to said at least one vertex.

152. The machine-readable medium of claim 146, wherein said canonical data comprises transactional canonical data.

153. The machine-readable medium of claim 152, wherein each of said transactional canonical data comprises no more than 3 transactional canonical data elements.

154. The machine-readable medium of claim 152, wherein said canonical data comprises relationship canonical data.

155. The machine-readable medium of claim 146, wherein said canonical data comprises relationship canonical data.

156. The machine-readable medium of claim 146, wherein said method is implemented in a computer system.

157. A machine-readable medium storing instructions that, if executed by a computer system, causes the computer system to perform method of modifying a data structure comprising the steps of:

(a) providing an inferential web comprising canonical data, said canonical data being organized into a plurality of nodes and at least one vertex connecting at least two connected nodes of said nodes, wherein said data structure comprises an inferential web that shows a user connections between at least two entities; and

(b) modifying said inferential web to form a modified inferential web.

158. The machine-readable medium of claim 157, wherein said method further comprises the step of displaying said modified inferential web to a user on a visual display apparatus.

159. The machine-readable medium of claim 157, wherein said method further comprises the step of storing said modified inferential web on a data storage medium.

160. The machine-readable medium of claim 157, wherein step (b) comprises assigning a weight to said at least one vertex.

161. The machine-readable medium of claim 157, wherein step (b) comprises modifying a weight of said at least one vertex.

162. The machine-readable medium of claim 157, wherein step (b) comprises assigning a direction to said at least one vertex.

163. The machine-readable medium of claim 157, wherein step (b) comprises modifying a direction of said at least one vertex.

164. The machine-readable medium of claim 157, wherein step (b) comprises collapsing at least a portion of said inferential web.

165. The machine-readable medium of claim 157, wherein step (b) comprises expanding at least a portion of said inferential web.

166. The machine-readable medium of claim 157, wherein step (b) comprises combining at least a portion of said inferential web with a second inferential web.

167. The machine-readable medium of claim 157, wherein step (b) comprises extracting at least a portion of said inferential web,

168. The machine-readable medium of claim 157, wherein at least some of said nodes are secure nodes.

169. The machine-readable medium of claim 157, wherein said at least two connected nodes comprises a plurality of connected nodes.

170. The machine-readable medium of claim 157, wherein said at least one vertex comprises a plurality of vertices.

171. The machine-readable medium of claim 157, wherein said inferential web is modified due to said inferential web being queried by said user.

172. The machine-readable medium of claim 157, wherein said canonical data comprises transactional canonical data.

173. The machine-readable medium of claim 172, wherein each of said transactional canonical data comprises no more than 3 transactional canonical data elements.

174. The machine-readable medium of claim 172, wherein said canonical data comprises relationship canonical data.

175. The machine-readable medium of claim 157, wherein said canonical data comprises relationship canonical data.

176. The machine-readable medium of claim 157, wherein said method is implemented in a computer system.

177. A machine-readable medium storing instructions that, if executed by a computer system, causes the computer system to perform a method of alerting a user if a data structure is modified comprising the steps of:

(a) providing an inferential web comprising canonical data, said canonical data being organized into a plurality of nodes and at least one vertex connecting at least two connected nodes of said nodes, wherein said data structure comprises an inferential web that shows a user connections between at least two entities; and

(b) alerting the user if said inferential web is modified to form a modified inferential web.

178. The machine-readable medium of claim 177, wherein said inferential web is modified by a weight being assigned to said at least one vertex.

179. The machine-readable medium of claim 177, wherein said inferential web is modified by a weight of said at least one vertex being modified.

180. The machine-readable medium of claim 177, wherein said inferential web is modified by a direction being assigned to said at least one vertex.

181. The machine-readable medium of claim 177, wherein said inferential web is modified by a direction of said at least one vertex being modified.

182. The machine-readable medium of claim 177, wherein said inferential web is modified by collapsing at least a portion of said inferential web.

183. The machine-readable medium of claim 177, wherein said inferential web is modified by expanding at least a portion of said inferential web.

184. The machine-readable medium of claim 177, wherein said inferential web is modified by combining at least a portion of said inferential web with a second inferential web.

185. The machine-readable medium of claim 177, wherein said inferential web is modified by extracting at least a portion of said inferential web,

186. The machine-readable medium of claim 177, wherein at least some of said nodes are secure nodes.

187. The machine-readable medium of claim 177, wherein said at least two connected nodes comprises a plurality of connected nodes.

188. The machine-readable medium of claim 177, wherein said at least one vertex comprises a plurality of vertices.

189. The machine-readable medium of claim 177, wherein said inferential web is modified due to said inferential web being queried by said user.

190. The machine-readable medium of claim 177, wherein said user is alerted by a visible alert.

191. The machine-readable medium of claim 177, wherein said user is alerted by an audible alert.

192. The machine-readable medium of claim 177, wherein said canonical data comprises transactional canonical data.

195. The machine-readable medium of claim 177, wherein said canonical data comprises relationship canonical data.

196. The machine-readable medium of claim 177, wherein said method is implemented in a computer system.