Content Clustering System and Method

Abstract

A computerized system and method are presented that creates implicit content on a mobile device by monitoring and recording input from sensors on the device. Metadata from the implicit content and from user-created content is then analyzed the purpose of event identification. Using the metadata and event identification, the content is created into clusters, which can be confirmed by the user as actual events. Events can then be grouped according to metadata and event information into a presentation grouping.

What is claimed is: 
     
         1 . A mobile communication device comprising:
 a) a processor that is controlled via programming instructions;   b) a non-transitory computer readable memory;   c) a user input device for receiving explicit input instructions from a user;   d) an optical sensor;   e) non-optical sensors selected from a group consisting of an accelerometer, a gyroscope, and a location identifying sensor;   f) explicit content generation programming stored on the memory and performed by the processor, the explicit content generation programming causing the processor to respond to an explicit input instruction from the user input device by storing image content on the memory, the image content including:
 i) an image file recorded by the optical sensor, and 
 ii) image time metadata indicating the time at which the image file was captured; 
   g) implicit content generation programming stored on the memory and performed by the processor, the implicit content generation programming causing the processor to:
 i) monitor the non-optical sensors; 
 ii) identify a change in the non-optical sensors; 
 iii) in response to the change in the non-optical sensors, storing implicit content on the memory, the implicit content including
 (1) an indication of the change in the non-optical sensors, and 
 (2) implicit time metadata identifying the time at which the change in the non-optical sensors was identified; 
 
   h) content clustering programming that groups the image content and the implicit content into a cluster based on similarities between the image time metadata and the implicit time metadata.