The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Sep. 16, 2014

Filed:

Jul. 24, 2013
Applicant:

Aro, Inc., Seattle, WA (US);

Inventors:

Alan Linchuan Liu, Seattle, WA (US);

Kevin Francis Eustice, Seattle, WA (US);

Andrew F. Hickl, Seattle, WA (US);

Assignee:

Aro, Inc., Seattle, WA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 17/28 (2006.01); G06F 17/27 (2006.01); G06F 17/30 (2006.01); G06N 5/02 (2006.01); H04W 4/20 (2009.01); H04W 4/02 (2009.01); G06N 99/00 (2010.01); G06Q 30/06 (2012.01);
U.S. Cl.
CPC ...
H04W 4/02 (2013.01); G06F 17/2785 (2013.01); G06F 17/30876 (2013.01); G06N 5/02 (2013.01); H04W 4/206 (2013.01); G06N 99/005 (2013.01); G06Q 30/0631 (2013.01);
Abstract

Embodiments create and label context slices from observation data that together define a storyline of a user's movements. A context is a (possibly partial) specification of what a user was doing in the dimensions of time, place, and activity. Contexts can vary in their specificity, their semantic content, and their likelihood. A storyline is composed of a time-ordered sequence of contexts that partition a given span of time. A storyline is created through a process of data collection, slicing and labeling. Raw context data can be collected from a variety of observation sources with various error characteristics. Slicing refines the chaotic collection of contexts produced by data collection into a single consistent storyline composed of a sequence of contexts representing homogeneous time intervals. Labeling adds more specific and semantically meaningful data (e.g., geography, venue, activity) to the storyline produced by slicing.


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