Learning a user's activity preferences from GPS traces and known nearby venues
First Claim
1. A method for inferring activities associated with a user, the method comprising:
- receiving a cluster of locations that indicates a location trace of the user during a period of time and corresponding context;
smoothing the location trace, which involves statistically removing a first subset of locations from the location cluster, and interpolating a second subset of locations into the location cluster;
deriving a set of venues based on the location cluster from a venue database, wherein a visit to a respective venue is identified as a hypothetical visit responsive to the venue being located within a location range which includes the received location cluster and being associated with the corresponding context;
deriving a set of activity types associated with the venues from a venue-to-activity mapping;
associating attributes of the venues to the activity types based on the corresponding context;
identifying a subset of the activity types of which the associated attributes are similar to a query context;
assigning a weight to each identified activity type based on similarity between its attributes and the query context; and
producing a probability distribution of various activity types based on the subset of the activity types and their weights, wherein the probability distribution predicts likelihoods that the user engages in each identified activity type associated with the query context and the location.
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Abstract
A method for inferring activities to a user is provided. The system receives at least one location trace and corresponding contextual information. The system then derives a set of venues based on a venue database, wherein a respective hypothetical visit is associated with the contextual information corresponding to the location trace. The system derives a set of activity types associated with a context based on the venues, the corresponding context indicated by the location trace, and a venue-to-activity mapping. In addition, the system receives a user query context and identifies a number of activity types of which the associated contextual information is similar to the user query context. The system further weights a respective identified activity type based on its associated context'"'"'s similarity to the user query context, normalizes weights associated with each identified activity type, and produces an activity-type probability distribution, thereby facilitating inferring activities associated with the user.
52 Citations
21 Claims
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1. A method for inferring activities associated with a user, the method comprising:
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receiving a cluster of locations that indicates a location trace of the user during a period of time and corresponding context; smoothing the location trace, which involves statistically removing a first subset of locations from the location cluster, and interpolating a second subset of locations into the location cluster; deriving a set of venues based on the location cluster from a venue database, wherein a visit to a respective venue is identified as a hypothetical visit responsive to the venue being located within a location range which includes the received location cluster and being associated with the corresponding context; deriving a set of activity types associated with the venues from a venue-to-activity mapping; associating attributes of the venues to the activity types based on the corresponding context; identifying a subset of the activity types of which the associated attributes are similar to a query context; assigning a weight to each identified activity type based on similarity between its attributes and the query context; and producing a probability distribution of various activity types based on the subset of the activity types and their weights, wherein the probability distribution predicts likelihoods that the user engages in each identified activity type associated with the query context and the location. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A non-transitory computer readable storage medium storing instructions which when executed by a computer cause the computer to perform a method for inferring activities associated with a user, the method comprising:
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receiving a cluster of locations that indicates a location trace of the user during a period of time and corresponding context; smoothing the location trace, which involves statistically removing a first subset of locations from the location cluster, and interpolating a second subset of locations into the location cluster; deriving a set of venues based on the location cluster from a venue database, wherein a visit to a respective venue is identified as a hypothetical visit responsive to the venue being located within a location range which includes the received location cluster and being associated with the corresponding context; deriving a set of activity types associated with the venues from a venue-to-activity mapping; associating attributes of the venues to the activity types based on the corresponding context; identifying a subset of the activity types of which the associated attributes are similar to a query context; assigning a weight to each identified activity type based on similarity between its attributes and the query context; and producing a probability distribution of various activity types based on the subset of the activity types and their weights, wherein the probability distribution predicts likelihoods that the user engages in each identified activity type associated with the query context and the location. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. A computer system for recommending leisure activities to a user, the computer system comprising:
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a memory; a processor; a location trace receiving mechanism that receives a cluster of locations that indicates a location trace of the user during a period of time and corresponding context; a location trace smoothing mechanism that smoothes the location trace, which involves statistically removing a first subset of locations from the location cluster, and interpolating a second subset of locations into the location cluster; a location trace preprocessing module coupled to the processor that; derives a set of venues based on the location cluster from a venue database, wherein a visit to a respective venue is identified as a hypothetical visit; responsive to the venue being located within a location range which includes the received location cluster and being associated with the corresponding context; derives a set of activity types associated with the venues from a venue-to-activity mapping; and associates attributes of the venues to the activity types based on the context; and an inferring mechanism coupled to the processor that; identifies a subset of the activity types of which the associated attributes are similar to a query context; assigns a weight to each identified activity type based on similarity between its attributes and the query context; and produces a probability distribution of various activity types based on the subset of the activity types and their weights, wherein the probability distribution predicts likelihoods that the user engages in each identified activity type associated with the query context and the location. - View Dependent Claims (16, 17, 18, 19, 20, 21)
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Specification