Using Aggregate Location Metadata to Provide a Personalized Service
First Claim
1. A training system, implemented using computing functionality, for generating item models for use in providing a personalized service, comprising:
- a data collection module for providing location-tagged data, the location-tagged data identifying one or more of;
sites that have been selected by a group of data-providing users with respect to respective locations of the data-providing users; and
queries that have been issued by the group of data-providing users with respect to respective locations of the data-providing users;
a data store for storing the location-tagged data;
an item model generation module for generating a plurality of item models based on the location-tagged data, the plurality of items models including one or more of;
at least one site model that estimates a probabilistic distribution of locations for an individual, given that the individual selects a particular site; and
at least one query model that estimates a probabilistic distribution of locations for the individual, given that the individual issues a particular query; and
a data store for storing one or more of said at least one site model and said at least one query model.
2 Assignments
0 Petitions
Accused Products
Abstract
Functionality is described herein which generates a plurality of item models based on the aggregate behavior of users, such as the aggregate behavior of the users in selecting network-accessible sites and/or issuing particular queries. In one implementation, each item model estimates a probabilistic distribution of locations for an individual, given that the individual selects a particular item (e.g., a particular site or query). The functionality can use the item models to provide a personalized service to an end user. For example, in one scenario, the functionality can generate a plurality of location-based features based on the item models. The functionality can then learn a ranking model based on the location-based features. In a real-time phase of operation, a query processing system uses the ranking model to personalize search results for an end user.
-
Citations
20 Claims
-
1. A training system, implemented using computing functionality, for generating item models for use in providing a personalized service, comprising:
-
a data collection module for providing location-tagged data, the location-tagged data identifying one or more of; sites that have been selected by a group of data-providing users with respect to respective locations of the data-providing users; and queries that have been issued by the group of data-providing users with respect to respective locations of the data-providing users; a data store for storing the location-tagged data; an item model generation module for generating a plurality of item models based on the location-tagged data, the plurality of items models including one or more of; at least one site model that estimates a probabilistic distribution of locations for an individual, given that the individual selects a particular site; and at least one query model that estimates a probabilistic distribution of locations for the individual, given that the individual issues a particular query; and a data store for storing one or more of said at least one site model and said at least one query model. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
-
-
11. A computer readable storage medium for storing computer readable instructions, the computer readable instructions providing a query processing system when executed by one or more processing devices, the computer readable instructions comprising:
-
logic configured to receive a query from an end user; logic configured to associate the query with an assessed location; logic configured to generate a group of query-time features based, in part, on at least one item model, said at least one item model estimating a probabilistic distribution of locations for an individual, given that the individual selects a particular item; and logic configured to use at least one ranking model, together with the query-time features, to provide at least one recommended item that is assessed as being suitable for the end user, given the assessed location that is associated with the end user. - View Dependent Claims (12)
-
-
13. A method, implemented using computing functionality, for providing a personalized service, comprising:
-
receiving user selection data which defines selections of items by a group of data-providing users; associating each instance of the user selection data with a metadata observation, to provide metadata-tagged data; storing the metadata-tagged data in a data store; generating at least one item model based on the metadata-tagged data, said at least one item model estimating a probabilistic distribution of metadata observations associated with an individual, given that the individual selects a particular item; storing said at least one item model in a data store; and applying said at least one item model to provide the personalized service to an end user, said receiving, associating, storing the metadata-tagged data, generating, storing said at least one item model, and applying being performed by the computing functionality. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20)
-
Specification