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A hierarchical behavioral profile

A profile, hierarchical technology, applied in marketing, data processing applications, instrumentation, etc., to solve problems such as limiting the predictive power of profiles

Inactive Publication Date: 2014-10-01
GOOGLE TECH HLDG LLC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This severely limits the predictive power of the profile

Method used

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  • A hierarchical behavioral profile
  • A hierarchical behavioral profile
  • A hierarchical behavioral profile

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Embodiment Construction

[0025] Turning to the drawings, wherein like reference numerals refer to like elements, the invention is shown implemented in a suitable environment. The following description is based on embodiments of the present invention and should not be construed as limiting the present invention to alternative embodiments not explicitly described herein.

[0026] Aspects of the invention can be found in figure 1 A representative communication environment 100 practiced. Users 102 use their communication devices 104 to perform various tasks, such as visiting websites 106, communicating with friends 108, running web-based applications for work or fun, shopping, and logging health information. While performing these activities, user 102 generates information about his behavior, preferences, health status, and social connections. Some of this information is explicitly generated when user 102 sets preferences in a profile. Other information may be suggestive, such as how often user 102 run...

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Abstract

In a hierarchical profile, each node represents at least one feature of behavioral data collected (300) about an entity (102) profiled, with the topmost node selected (306) as the "statistically most informative" feature of the data. A profile can cover numerous domains and be predictively very powerful in each domain. A number of observations can be "aggregated" (316) together into a single datapoint. In use, the structure of the profile is compared (402) against current information associated with the entity to produce (406) a recommendation or prediction. If the profile represents at least some data aggregation, then new observations (500) are folded (504a, 504b, 504c) into the profile based on statistical weights of the aggregations. Because of the way the profile is created and updated, its hierarchical structure maps the collected observations. Therefore, as new observations are incorporated, if the new observations change (600a) the profile's structure significantly, then it can be hypothesized (602) that something "interesting" has happened to the entity.

Description

technical field [0001] The present invention relates generally to personal computers and, more particularly, to profiling the behavior of computer users. Background technique [0002] As personal communication devices (eg, cell phones) are developed to support more and more functions, people use these functions for far more than talking. As we all know, these devices now typically allow their users to visit websites, run web-based applications, create media files (for example, by using the camera on the device to take photos or record w's web interface) to download media files. In the course of these activities, users generate a wealth of information about their preferences and behavior. Some of this information is explicitly generated when the user sets preferences in the profile. Other information may be implied, such as how often a user runs a particular application. [0003] Advertisers and other commercial entities recognize how valuable this information is, both ex...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06Q30/02
CPCG06Q30/0269
Inventor 昊国华李建国保罗·C·戴维斯罗伯特·S·维特
Owner GOOGLE TECH HLDG LLC
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