INTERACTIVE MACHINE LEARNING ADVICE FACILITY

• US 20090119234A1
• Filed: 10/31/2008
• Published: 05/07/2009
• Est. Priority Date: 11/02/2007
• Status: Active Grant

• Current Assignee: eBay Inc.
• Original Assignee: Hunch Inc. (eBay Inc.)
• Inventors: PINCKNEY, Thomas, DIXON, Chris, GATTIS, Matthew Ryan
• Granted Patent: US 7,958,066 B2
• Time in Patent Office: Days
• US Class Current: 706/12
• CPC Class Codes: G06N 20/00 Machine learning

Abstract

In embodiments of the present invention improved capabilities are described for helping a user make a decision through the use of a machine learning facility. The process may begin with an initial question being received by the machine learning facility from the user. The user may then be provided with a dialog consisting of questions from the machine learning facility and answers provided by the user. The machine learning facility may then provide a decision to the user based on the dialog and pertaining to the initial question, such as a recommendation, a diagnosis, a conclusion, advice, and the like. In embodiments, future questions and decisions provided by the machine learning facility may be improved through feedback provided by the user.

Claims

1-114. -114. (canceled)

115. A method of helping a user make a decision through the use of a machine learning facility, comprising:

receiving an initial question from the user;

providing the user with a dialog consisting of questions from the machine learning facility and answers provided by the user;

providing a decision to the user from the machine learning facility, wherein the decision is based on the dialog and pertaining to the initial question; and

receiving feedback from the user to improve future questions and decisions provided by the machine learning facility.

116. The method of claim 115, wherein the decision is a recommendation.

117. The method of claim 115, wherein the decision is a diagnosis.

118. The method of claim 115, wherein the initial question is associated with one of a broad category of topics.

119. The method of claim 118, wherein at least one of the broad category of topics is a product.

120. The method of claim 118, wherein at least one of the broad category of topics is personal.

121. The method of claim 118, wherein at least one of the broad category of topics is health.

122. The method of claim 118, wherein at least one of the broad category of topics is business.

123. The method of claim 118, wherein at least one of the broad category of topics is political.

124. The method of claim 118, wherein at least one of the broad category of topics is educational.

125. The method of claim 118, wherein at least one of the broad category of topics is entertainment.

126. The method of claim 118, wherein at least one of the broad category of topics is environment.

127. The method of claim 115, wherein the question is about the user.

128. The method of claim 115, wherein at least one of the question and the decision includes at least one image.

129. The method of claim 115, wherein the question is not asked directly to the user, but rather determined from contextual information.

130. The method of claim 115, wherein the dialog continues until the machine learning facility develops a high confidence in a reduced set of decisions.

131. The method of claim 115, wherein the decision displays a ranking of decision choices.

132. The method of claim 115, wherein the decision is a pseudo random decision on the chance that the pseudo random decision turns out to be useful.

133. A method of helping a user make a decision through the use of a computing facility, comprising:

receiving an initial question from the user;

providing the user with a dialog consisting of questions from the computing facility and answers provided by the user;

providing the decision to the user from the computing facility, wherein the decision is based on an aggregated feedback from a plurality of users; and

improving future questions and decisions provided by the computing facility based on receiving feedback from the user.

134. A system to help a user make a decision through the use of a machine learning facility, comprising:

the machine learning facility receiving an initial question from the user;

a dialog facility within the machine learning facility providing the user with questions and accepting answers from the user;

the machine learning facility providing a decision to the user, wherein the decision is based on the exchange between the user and the machine learning facility and pertaining to the initial question; and

the machine learning facility receiving feedback from the user to improve future questions and decisions provided by the machine learning facility.