Abstract: A system receives event information describing an event performed by a user with a content provider. The system identifies a property associated with the content provider whose aggregation conditions are satisfied by the event. The system selects an aggregator to which to send the information based on the user. The selected aggregator stores an event entry in its aggregator store with the event information and an indication of the property. The aggregator determines an aggregate value of the user for the property based on event entries in the aggregator store associated with the user and the property. The system provides a content item associated with the content provider to the user based on audience conditions of the property being satisfied by the aggregate value. The system also determines a removal time for each event entry and schedules an aggregation event for updating the user's aggregate value at removal time.

Abstract: A system receives event information describing an event performed by a user with a content provider. The system identifies a property associated with the content provider whose aggregation conditions are satisfied by the event. The system selects an aggregator to which to send the information based on the user. The selected aggregator stores an event entry in its aggregator store with the event information and an indication of the property. The aggregator determines an aggregate value of the user for the property based on event entries in the aggregator store associated with the user and the property. The system provides a content item associated with the content provider to the user based on audience conditions of the property being satisfied by the aggregate value. The system also determines a removal time for each event entry and schedules an aggregation event for updating the user's aggregate value at removal time.

Abstract: An online system uses rules and/or machine learning models to provide travel related content items to users. The online system may determine when a user is likely to travel and provide the content items in advance of a trip. The online system may also provide content items during a trip that indicate modifications to the user's itinerary, for example, adding a rental car, upgrading a flight ticket, or upgrading a hotel room. Further, the online system may provide a content item after a user has checked out of a hotel that describes a loyalty program of the hotel. In one example, the online system trains machine learning models using feature vectors derived based on trips taken by a population of users of the online system and itinerary information from third parties. The content items may be generated based on information provided from the third parties.

Abstract: A system receives event information describing an event performed by a user with a content provider. The system identifies a property associated with the content provider whose aggregation conditions are satisfied by the event. The system selects an aggregator to which to send the information based on the user. The selected aggregator stores an event entry in its aggregator store with the event information and an indication of the property. The aggregator determines an aggregate value of the user for the property based on event entries in the aggregator store associated with the user and the property. The system provides a content item associated with the content provider to the user based on audience conditions of the property being satisfied by the aggregate value. The system also determines a removal time for each event entry and schedules an aggregation event for updating the user's aggregate value at removal time.

Abstract: A system receives event information describing an event performed by a user with a content provider. The system identifies a property associated with the content provider whose aggregation conditions are satisfied by the event. The system selects an aggregator to which to send the information based on the user. The selected aggregator stores an event entry in its aggregator store with the event information and an indication of the property. The aggregator determines an aggregate value of the user for the property based on event entries in the aggregator store associated with the user and the property. The system provides a content item associated with the content provider to the user based on audience conditions of the property being satisfied by the aggregate value. The system also determines a removal time for each event entry and schedules an aggregation event for updating the user's aggregate value at removal time.

Abstract: Online system users interact with one or more third party systems, with the online system maintaining an account for each of its users and each third party system maintaining a third party account for each of its users. The online system compares information in a user's account to accessible information in third party accounts and establishes connections between the user's account and o third party accounts based on the comparisons. A connection between the user's account and a third party account includes a confidence level indicating a likelihood of the third party account being associated with the user of the online system corresponding to the account. A third party system may request information from the online system about a user specifying a threshold confidence level, allowing the online system to return information from third party accounts having connections to the user's account with at least the threshold confidence level.

Abstract: Online system users interact with one or more third party systems, with the online system maintaining an account for each of its users and each third party system maintaining a third party account for each of its users. The online system compares information in a user's account to accessible information in third party accounts and establishes connections between the user's account and o third party accounts based on the comparisons. A connection between the user's account and a third party account includes a confidence level indicating a likelihood of the third party account being associated with the user of the online system corresponding to the account. A third party system may request information from the online system about a user specifying a threshold confidence level, allowing the online system to return information from third party accounts having connections to the user's account with at least the threshold confidence level.