Scalable spatiotemporal clustering of heterogeneous events

Patent metadata

Field	Value
Publication number	US-9230216-B2
Application number	US-201313890139-A
Country	US
Kind code	B2
Filing date	May 8, 2013
Priority date	May 8, 2013
Publication date	Jan 5, 2016
Grant date	Jan 5, 2016

Abstract

One embodiment of the present invention provides a system for clustering heterogeneous events. During operation, the system finds a partition of events into clusters such that each cluster includes a set of events. In addition, the system estimates probability distributions for various properties of events associated with each cluster. The system obtains heterogeneous event data, and analyzes the heterogeneous event data to determine the distribution of event properties associated with clusters and to assign events to clusters.

First claim

What is claimed is:

1. A computer-executable method, comprising:
determining a prior distribution of a cluster index variable for event assignments, wherein the prior distribution includes a hyperparameter that describes the mean and variance for the cluster index variable;
determining a property-specific prior distribution for a respective event property, wherein the property-specific prior distribution includes a property-specific hyperparameter that describes the mean and variance for the respective event property;
obtaining heterogeneous event data that corresponds to two or more heterogeneous event types;
generating, based on the property-specific prior distribution for the respective event property and the property-specific hyperparameter, event property clusters for a respective event property of a plurality of event properties, wherein the respective event property is probabilistically dependent on the cluster index variable;
generating two or more different event type clusters for the heterogeneous event types, wherein a respective event type cluster is associated with a plurality of event property clusters, a respective event has an event type, an event type is an event property, and the respective event is represented by one or more event properties; and
assigning events from the heterogeneous event data to the two or more different event type clusters and the event property clusters.

2. The method of claim 1 , wherein a respective event property is one of: event time, event location, event type, event description, event location properties, or event time properties.

3. The method of claim 2 , wherein the event location properties indicate whether the location is urban, rural, or near or far from a road.

4. The method of claim 2 , wherein the event time properties indicate whether the event time is day, night, weekend, or weekday.

5. The method of claim 1 , further comprising:
analyzing the heterogeneous event data to determine the distribution of event properties associated with clusters using a joint probability distribution that factorizes as follows:

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Assignees

• Palo Alto Res Ct Inc

Inventors

• Bart Evgeniy
• Price Robert R

Classifications

• G06N5/022 Primary

  Knowledge engineering; Knowledge acquisition · CPC title