Microsoft Technology Licensing, LLC

Ramaswamy Hariharan

Eric J Horvitz

John Charles Krumm

Kentaro Toyama

John R Douceur

Ross Garrett Cutler

Daniel Chaim Robbins

Matthew Uyttendaele

Nuria M Oliver

Eric K Ringger

Described are methods that utilize a geographic location technology (e.g., GPS) to determine user location data, and existing network-based websites (e.g., Internet websites) for searching and accessing data related to the location data such that the user context can be developed and stored. A location component is provided that determines location data of a wireless communications device of a user. A context component is provided that accesses context data based on the location data to define a context in which the device is located. Activities, goals, and overall context of a user can be inferred through statistical fusion of multiple sources of evidence. The context data is presented to the user via the wireless device such that the user can make decisions as to where to go, for example. User preferences can be accessed and applied to filter context data according to what the user desires to see and access.

Integration of location logs, GPS signals, and spatial resources for identifying user activities, goals, and context

A location history is a collection of locations over time for an object. A stay is a single instance of an object spending some time in one place, and a destination is any place where one or more objects have experienced a stay. Location histories are parsed using stays and destinations. In a described implementation, each location of a location history is recorded as a spatial position and a corresponding time at which the spatial position is acquired. Stays are extracted from a location history by analyzing locations thereof with regard to a temporal threshold and a spatial threshold. Specifically, two or more locations are considered a stay if they exceed a minimum stay duration and are within a maximum roaming distance. Each stay includes a location, a starting time, and an ending time. Destinations are produced from the extracted stays using a clustering operation and a predetermined scaling factor.

Parsing location histories

A location history is a collection of locations over time for an object. By applying a recurring time period to a location history, it can be converted into a stochastic model of the location history. For example, a location history can be reorganized based on intervals that subside a recurring cycle. In a described implementation, training a location history model involves traversing each interval of multiple cycles of a target location history. After each object location at each interval is entered into a training matrix, the intervals can be normalized to determine relative probabilities per location for each interval of a designated cycle. The training and resulting location history model can be Markovian or non-Markovian. Applications include probabilistic location estimation, fusion of location estimates, location-history simulation, optimal scheduling, transition analysis, clique analysis, and so forth.

Modeling location histories

Methods and systems that determine automatically the likelihood that a device is inside or outside of a structure or building. The system uses one or more sensors to detect ambient conditions, and make the determination. The inference can be used to save power or suppress services from certain devices, which are irrelevant, cannot be used effectively, or do not function under certain circumstances. In support thereof, the system includes one or more context sensors that measure parameters associated probabilistically with the context of a device. A context computing component considers one or more context sensors and facilitates determination of ideal actions, policies, and situations associated with the device. A service provided by the subject invention is the inference from one or more available observations the probability that the device is inside versus outside.

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Irvine, CA, United States of America

Ramaswamy Hariharan