Predicting or recommending a users future location based on crowd data
First Claim
Patent Images
1. A computer-implemented method comprising:
- generating a prediction basis for a user comprising previous crowd data describing crowds in which the user was previously included during a plurality of reoccurring time windows; and
predicting one or more future locations of the user based on the prediction basis, wherein predicting the one or more future locations of the user based on the prediction basis comprises;
obtaining current crowd data describing a current crowd in which the user is currently included;
obtaining relevant crowd data from the prediction basis; and
determining whether the user is likely to move to one of the one or more future locations based on a comparison of the current crowd data and at least a subset of the relevant crowd data from the prediction basis.
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Abstract
A system and method for predicting a future location of a user are provided. In general, a prediction basis including crowd data describing crowds in which a user was included during a number of reoccurring time windows is generated. Each reoccurring time window may be, for example, a day of the week (i.e., Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, or Sunday), a portion of a day of the week (e.g., Monday Morning, Monday Afternoon, Monday Evening, Tuesday Evening, etc.), a day of the month (e.g., 1st day of the month), a day of the year (e.g., March 25th), or the like. The prediction basis of the user is then used to predict one or more future locations of the user.
165 Citations
32 Claims
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1. A computer-implemented method comprising:
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generating a prediction basis for a user comprising previous crowd data describing crowds in which the user was previously included during a plurality of reoccurring time windows; and predicting one or more future locations of the user based on the prediction basis, wherein predicting the one or more future locations of the user based on the prediction basis comprises; obtaining current crowd data describing a current crowd in which the user is currently included; obtaining relevant crowd data from the prediction basis; and determining whether the user is likely to move to one of the one or more future locations based on a comparison of the current crowd data and at least a subset of the relevant crowd data from the prediction basis. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30)
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31. A server comprising:
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a communication interface communicatively coupling the server to a network; and a controller associated with the communication interface and adapted to; generate a prediction basis for a user comprising previous crowd data describing crowds in which the user was previously included during a plurality of reoccurring time windows; and predict one or more future locations of the user based on the prediction basis, wherein when predicting the one or more future locations of the user based on the prediction basis, the controller is adapted to; obtain current crowd data describing a current crowd in which the user is currently included; obtain relevant crowd data from the prediction basis; and determine whether the user is likely to move to one of the one or more future locations based on a comparison of the current crowd data and at least a subset of the relevant crowd data from the prediction basis.
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32. A non-transitory computer-readable medium storing software for instructing a controller of a computing device to:
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generate a prediction basis for a user comprising previous crowd data describing crowds in which the user was previously included during a plurality of reoccurring time windows; and predict one or more future locations of the user based on the prediction basis, wherein when predicting the one or more future locations of the user based on the prediction basis the software for instructing a controller further instructs the controller of the computing device to; obtain current crowd data describing a current crowd in which the user is currently included; obtain relevant crowd data from the prediction basis; and determine whether the user is likely to move to one of the one or more future locations based on a comparison of the current crowd data and at least a subset of the relevant crowd data from the prediction basis.
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Specification