Patent application number | Description | Published |
20120239486 | SUGGESTING DEALS TO A USER IN A SOCIAL NETWORKING SYSTEM - A social networking system suggests deals relevant to a user. The deals are selected for suggestion based on social information associated with the user. Social information used for selecting candidate deals for a user includes information describing other users connected to the user and their associations with the candidate deals or with related deals, for example, deals from the same provider. Associations of connections of the user with the candidate deals may be determined based on actions associated with the candidate deals performed by the connections. The actions performed by the connections may be weighted based on types of the actions to determine a measure of relevance of the candidate deal for the user. Candidate deals are selected from a set of deals by applying deal targeting criteria received from deal providers. The deal targeting criteria specify attributes describing users to be targeted for a particular deal. | 09-20-2012 |
20130080523 | INSTANTANEOUS RECOMMENDATION OF SOCIAL INTERACTIONS IN A SOCIAL NETWORKING SYSTEM - As a user of a social networking system views a page that includes information provided by the system, certain types of social interactions are monitored. If an interaction monitored for is detected, at least one recommendation unit is identified to present to user on the page. The recommendation unit is identified based on a description of the interaction. The recommendation unit suggests that the user perform a social interaction in the social networking system. The recommendation unit is transmitted to a device of the user and is presented to the user on the page without having to reload the entire page. | 03-28-2013 |
20130080524 | INSTANTANEOUS RECOMMENDATION OF SOCIAL INTERACTIONS IN A SOCIAL NETWORKING SYSTEM - When a social interaction by a user in a social networking system is detected, a description of the interaction is created. A service level auction is performed to select one or more service modules to provide recommendation units from a plurality of service modules. Each of the plurality of service modules is configured to provide recommendation units that suggest that the user engage in a social interaction in the social networking system. The description of the interaction is provided to each service module selected and recommendation units are requested. A plurality of recommendation units are received from the selected service modules. A unit level auction is performed to select one of more recommendation units to present to the user from the plurality of recommendation units. The selected recommendation units are transmitted to a device of the user for presentation. | 03-28-2013 |
20130124298 | GENERATING CLUSTERS OF SIMILAR USERS FOR ADVERTISEMENT TARGETING - A social networking system may identify a first set of users as part of a training cluster and identify a second set of users that is similar to the first set of users for purposes of targeting advertisements related to the advertiser. Using past engagement history (e.g., click-through rates), demographic information, and keywords associated with the training cluster of users, a social networking system may generate a training model specific to the training cluster. Confidence scores may be used to identify similar users across the total population of users of the social networking system for creating a targeting cluster of users for the advertisement. A revenue sharing scheme may be used induce page administrators to increase their fan base by enabling advertisers to target advertisements to users that have expressed interest in pages associated with the page administrators. | 05-16-2013 |
20130151539 | Real-Time Online-Learning Object Recommendation Engine - In one embodiment, a system includes one or more computing systems that implement a social networking environment containing a large number of heterogeneous objects type, each of the plurality of object types having varying features, the system implementing a generic object recommendation engine for scoring objects and recommending the objects to users of the social networking system. In particular embodiments, the user and content object features are fed as inputs into a heuristic model that generates an expected value for the content object and user. In particular embodiments, the object recommendation engine includes an online learner that may log a user's actions after the initial impression to determine the relatively degree of interest to the user. | 06-13-2013 |
20130173611 | GENERATION OF NICKNAME DICTIONARY - Methods, apparatuses and systems for generating a name-word dictionary that includes associations between names of users and candidate words (e.g., nicknames) based on statistical analysis of user communications observed at a network communications facility, such as a social network system, an email provider and the like. | 07-04-2013 |
20130325755 | METHODS AND SYSTEMS FOR OPTIMIZING MESSAGES TO USERS OF A SOCIAL NETWORK - Techniques to optimize messages sent to a user of a social networking system. In one embodiment, information about the user may be collected by the social networking system. The information may be applied to train a model for determining likelihood of a desired action by the user in response to candidate messages that may be provided for the user. The social networking system may provide to the user a message from the candidate messages with a selected likelihood of causing the desired action. | 12-05-2013 |
20140019233 | UNIFIED AUCTION MODEL FOR SUGGESTING RECOMMENDATION UNITS AND AD UNITS - A social networking system presents advertisements and recommendation units to its users. The recommendation units suggest actions for the users to increase their engagement with the social networking system or otherwise interact with other users, while the social networking system receives revenue from advertisers for displaying advertisements based on bid values associated with the advertisements. The social networking system determines values for the advertisements and for the recommendation units, where the values are measured in a comparable fashion. This allows the system to rank and select the advertisements and recommendation units together in a unified auction model. For example, the social networking system uses a pacing value to determine values of recommendation units having a common unit of measurement with expected values of advertisements to the social networking system. | 01-16-2014 |
20140108550 | INSTANTANEOUS RECOMMENDATION OF SOCIAL INTERACTIONS IN A SOCIAL NETWORKING SYSTEM - As a user of a social networking system views a page that includes information provided by the system, certain types of social interactions are monitored. If an interaction monitored for is detected, at least one recommendation unit is identified to present to user on the page. The recommendation unit is identified based on a description of the interaction. The recommendation unit suggests that the user perform a social interaction in the social networking system. The recommendation unit is transmitted to a device of the user and is presented to the user on the page without having to reload the entire page. | 04-17-2014 |
20150074215 | Methods And Systems For Optimizing Messages To Users Of A Social Network - Techniques to optimize messages sent to a user of a social networking system. In one embodiment, information about the user may be collected by the social networking system. The information may be applied to train a model for determining likelihood of a desired action by the user in response to candidate messages that may be provided for the user. The social networking system may provide to the user a message from the candidate messages with a selected likelihood of causing the desired action. | 03-12-2015 |