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:
Jan. 03, 2017

Filed:

Dec. 31, 2014
Applicant:

Microsoft Technology Licensing, Llc., Redmond, WA (US);

Inventors:

Yu Zheng, Beijing, CN;

Xing Xie, Beijing, CN;

Assignee:
Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G08G 1/01 (2006.01); G06K 9/46 (2006.01); G06F 19/00 (2011.01);
U.S. Cl.
CPC ...
G06K 9/00624 (2013.01); G06K 9/00476 (2013.01); G06K 9/46 (2013.01); G08G 1/0112 (2013.01); G08G 1/0133 (2013.01); G06K 2009/4666 (2013.01);
Abstract

Techniques for detecting outliers in data and determining spatiotemporal causal interactions in the data are discussed. A process collects global positioning system (GPS) points in logs and identifies geographical locations to represent the area where the service vehicles travelled with a passenger. The process models traffic patterns by: partitioning the area into regions, segmenting the GPS points from the logs into time bins, and identifying the GPS points associated with transporting the passenger. The process projects the identified GPS points onto the regions to construct links connecting GPS points located in two or more regions. Furthermore, the process builds a three-dimensional unit cube to represent features of each link. The points farthest away from a center of data cluster are detected as outliers, which represent abnormal traffic patterns. The process constructs outlier trees to evaluate relationships of the outliers and determines the spatiotemporal causal interactions in the data.


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