Mining life pattern based on location history
First Claim
1. A method comprising:
- under control of one or more processors configured with executable instructions;
collecting location data associated with an individual;
extracting a plurality of locations from the location data and transforming the plurality of locations in the location data to a plurality of stay points, each stay point comprising one or more locations of the plurality of locations that define a geographical region in which the individual has stayed within a predetermined distance over a predetermined time period;
clustering the plurality of stay points into a sequence of stay point clusters, each stay point cluster comprising stay points corresponding to a same place or sharing a same semantic meaning within a specific distance threshold;
creating a location history of the individual with the sequence of stay point clusters;
predicting a life pattern of the individual based at least in part on the location history, the life pattern emphasizing places significant to the individual and ignoring transitions between the significant places;
generating a life associate rule based on the life pattern, the life associate rule comprising a rule describing a relationship between two non-conditional life patterns and a support value representing a probability of co-occurrence of the two non-conditional life patterns; and
providing information to the individual based at least in part on the life pattern or the life associate rule.
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Accused Products
Abstract
Techniques for providing mining life pattern are described. This disclosure describes mining a life pattern of an individual, for example, by identifying places visited during the individual'"'"'s daily activities. Mining the individual life pattern includes collecting location data for the individual and predicting behaviors and preferences of the individual based at least in part on a location history. The location history of the individual is represented with a sequence of geographical regions that have been visited by the individual with corresponding arrival and departure times for each region. Once the life pattern is predicted from the location history, information is recommended to the individual based at least in part on the life pattern.
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Citations
18 Claims
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1. A method comprising:
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under control of one or more processors configured with executable instructions; collecting location data associated with an individual; extracting a plurality of locations from the location data and transforming the plurality of locations in the location data to a plurality of stay points, each stay point comprising one or more locations of the plurality of locations that define a geographical region in which the individual has stayed within a predetermined distance over a predetermined time period; clustering the plurality of stay points into a sequence of stay point clusters, each stay point cluster comprising stay points corresponding to a same place or sharing a same semantic meaning within a specific distance threshold; creating a location history of the individual with the sequence of stay point clusters; predicting a life pattern of the individual based at least in part on the location history, the life pattern emphasizing places significant to the individual and ignoring transitions between the significant places; generating a life associate rule based on the life pattern, the life associate rule comprising a rule describing a relationship between two non-conditional life patterns and a support value representing a probability of co-occurrence of the two non-conditional life patterns; and providing information to the individual based at least in part on the life pattern or the life associate rule. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A storage device encoded with instructions that, when executed by one or more processors, configure the one or more processors to perform acts comprising:
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collecting location data associated with an individual; extracting a plurality of locations from the location data and transforming the plurality of locations in the location data to a plurality of stay points, each stay point comprising one or more locations of the plurality of locations that define a geographical region in which the individual has stayed within a predetermined distance over a predetermined time period; clustering the plurality of stay points into a sequence of stay point clusters, each stay point cluster comprising stay points corresponding to a same place or sharing a same semantic meaning within a specific distance threshold; creating a location history of the individual with the sequence of stay point clusters; predicting a life pattern of the individual based at least in part on the location history, the life pattern emphasizing places significant to the individual and ignoring transitions between the significant places; generating a life associate rule based on the life pattern, the life associate rule comprising a rule describing a relationship between two non-conditional life patterns and a support value representing a probability of co-occurrence of the two non-conditional life patterns; and providing information to the individual based at least in part on the life pattern or the life associate rule. - View Dependent Claims (8, 9, 10, 11, 12)
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13. A system comprising:
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memory; one or more processors coupled to the memory to perform acts comprising; collecting location data associated with an individual; extracting a plurality of locations from the location data and transforming the plurality of locations in the location data to a plurality of stay points, each stay point comprising one or more locations of the plurality of locations that define a geographical region in which the individual has stayed within a predetermined distance over a predetermined time period; clustering the plurality of stay points into a sequence of stay point clusters, each stay point cluster comprising stay points corresponding to a same place or sharing a same semantic meaning within a specific distance threshold; creating a location history of the individual with the sequence of stay point clusters; predicting a life pattern of the individual based at least in part on the location history, the life pattern emphasizing places significant to the individual and ignoring transitions between the significant places; generating a life associate rule based on the life pattern, the life associate rule comprising a rule describing a relationship between two non-conditional life patterns and a support value representing a probability of co-occurrence of the two non-conditional life patterns; and providing information to the individual based at least in part on the life pattern or the life associate rule. - View Dependent Claims (14, 15, 16, 17, 18)
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Specification