Body Position-based Recommender System

Abstract

A body position-based recommender system infers user preferences from user behaviors and generates adaptive recommendations based upon the inferred user preferences and user body position information. The adaptive recommendations may be delivered kinesthetically. The inferences of user preferences may be based upon mobility inferences. The inferred preferences may be based upon the application of inference weightings that are determined in accordance with usage behavior priority rules that are applied to the user behaviors. Computer-implemented neural networks may be applied to infer user preferences from pictorial-based information. Natural language-based explanations that include the reasoning for the recommendations may be delivered to the user.

What is claimed is: 
     
         1 . A computer-implemented method, comprising:
 accessing automatically information comprising a body position of a user, wherein the information is determined by a positionally-aware device;   inferring automatically a user preference from a plurality of user behaviors;   generating automatically an adaptive recommendation that is based upon the inferred user preference and the body position information; and   delivering automatically the recommendation to the user.   
     
     
         2 . The method of  claim 1 , further comprising:
 inferring automatically the user preference from the plurality of user behaviors, wherein one behavior of the plurality of behaviors is a direction of gaze of the user.   
     
     
         3 . The method of  claim 1 , further comprising:
 inferring automatically the user preference from the plurality of user behaviors, wherein the inferring of the preference is based upon the application of a plurality of inference weightings that are determined in accordance with usage behavior priority rules that are applied to the plurality of user behaviors.   
     
     
         4 . The method of  claim 1 , further comprising:
 inferring automatically the user preference, wherein the user preference is inferred from an automatic analysis of pictorial-based information, wherein the automatic analysis is performed through application of a computer-implemented neural network.   
     
     
         5 . The method of  claim 1 , further comprising:
 delivering automatically the recommendation to the user, wherein the recommendation is delivered kinesthetically.   
     
     
         6 . The method of  claim 5 , further comprising:
 delivering automatically the recommendation, wherein the recommendation comprises an appliance self-propelling.   
     
     
         7 . The method of  claim 1 , further comprising:
 delivering automatically to the user an explanation for the recommendation, wherein the explanation is in a natural language format and comprises reasoning for the recommendation.   
     
     
         8 . A computer-implemented system comprising one or more processors configured to:
 access automatically information comprising a body position of a user, wherein the information is determined by a positionally-aware device;   infer automatically a user preference from a plurality of user behaviors;   generate automatically an adaptive recommendation that is based upon the inferred user preference and the body position information; and   deliver automatically the recommendation to the user.   
     
     
         9 . The system of  claim 8  comprising the one or more processors, further configured to:
 infer automatically the user preference from the plurality of user behaviors, wherein the inference of the user preference is based upon a mobility inference. 
 
     
     
         10 . The system of  claim 8  comprising the one or more processors, further configured to:
 infer automatically the user preference from the plurality of user behaviors, wherein the preference is inferred based upon the application of a plurality of inference weightings that are determined in accordance with usage behavior priority rules that are applied to the plurality of user behaviors. 
 
     
     
         11 . The system of  claim 8  comprising the one or more processors, further configured to:
 infer automatically the user preference, wherein the preference is inferred from an automatic analysis of pictorial-based information, wherein the automatic analysis is performed through application of a computer-implemented neural network. 
 
     
     
         12 . The system of  claim 8  comprising the one or more processors, further configured to:
 deliver automatically the recommendation to the user, wherein the recommendation is delivered kinesthetically. 
 
     
     
         13 . The system of  claim 12  comprising the one or more processors, further configured to:
 deliver automatically the recommendation, wherein the recommendation comprises an appliance self-propelling. 
 
     
     
         14 . The system of  claim 8  comprising the one or more processors, further configured to:
 deliver automatically an explanation for the recommendation, wherein the explanation is in a natural language format and comprises reasoning for the recommendation. 
 
     
     
         15 . An appliance comprising one or more processors configured to:
 access automatically information comprising a body position of a user, wherein the information is determined by a positionally-aware device;   infer automatically a user preference from a plurality of user behaviors;   generate automatically an adaptive recommendation that is based upon the inferred user preference and the body position information; and   deliver automatically the recommendation to the user.   
     
     
         16 . The appliance of  claim 15  comprising the one or more processors, further configured to:
 infer automatically the user preference from the plurality of user behaviors, wherein the inference of the user preference is based upon a mobility inference. 
 
     
     
         17 . The appliance of  claim 16  comprising the one or more processors, further configured to:
 infer automatically the user preference from the plurality of user behaviors, wherein the inference of the user preference is based upon the mobility inference, wherein the mobility inference is based upon information from a global positioning system receiver. 
 
     
     
         18 . The appliance of  claim 15  comprising the one or more processors, further configured to:
 infer automatically the user preference from the plurality of user behaviors, wherein the preference is inferred based upon the application of a plurality of inference weightings that are determined in accordance with usage behavior priority rules that are applied to the plurality of user behaviors. 
 
     
     
         19 . The appliance of  claim 15  comprising the one or more processors, further configured to:
 infer automatically the user preference, wherein the preference is inferred from an automatic analysis of pictorial-based information, wherein the automatic analysis is performed through application of a computer-implemented neural network. 
 
     
     
         20 . The appliance of  claim 15  comprising the one or more processors, further configured to:
 deliver automatically the recommendation to the user, wherein the recommendation comprises the appliance self-propelling.