Abstract: Methods and systems for extracting intents and intent profiles of users, as inferred from the different activities they execute and data they share on social media sites, and then (i) monetization of such intents via targeted advertisements, and (ii) enhancement of user experience via organization of their contact lists and conversations and posts based on their content and conceptual context.

Abstract: Methods and systems for extracting intents and intent profiles of users, as inferred from the different activities they execute and data they share on social media sites, and then (i) monetization of such intents via targeted advertisements, and (ii) enhancement of user experience via organization of their contact lists and conversations and posts based on their content and conceptual context.

Abstract: Methods and systems for extracting intents and intent profiles of users, as inferred from the different activities they execute and data they share on social media sites, and then (i) monetization of such intents via targeted advertisements, and (ii) enhancement of user experience via organization of their contact lists and conversations and posts based on their content and conceptual context.

Abstract: Methods and systems for extracting intents and intent profiles of users, as inferred from the different activities they execute and data they share on social media sites, and then (i) monetization of such intents via targeted advertisements, and (ii) enhancement of user experience via organization of their contact lists and conversations and posts based on their content and conceptual context.

Abstract: Methods and systems for integrating images with the associated text-based content signals and data about users' preferences to determine an image or user intent. Methods and implementations for monetizing these images is also described.

Abstract: Methods and systems for extracting intents and intent profiles of users, as inferred from the different activities they execute and data they share on social media sites, and then (i) monetization of such intents via targeted advertisements, and (ii) enhancement of user experience via organization of their contact lists and conversations and posts based on their content and conceptual context.

Abstract: Methods and systems are provided for constructing and using an advertisement performance model to predict performances of variations of an advertisement, and to recommend a variation with a better predicted performance than other variations. The advertisement model is constructed utilizing historical advertisement performance information, and is based at least in part on specified model parameters and advertisement parameters. Each variation of the advertisement includes a unique set of advertisement parameter values.

Abstract: Systems and methods for balancing goal guarantees and optimization of revenue in advertisement delivery under uneven, volatile traffic conditions are discloses. Generally, an advertisement delivery request is received. Using tolerance bands, a first plurality of advertisements served on a guaranteed number of impressions basis that may be served in response to the advertisement request is identified. Each advertisement of the first plurality of advertisements is delivering above a lower bound of a tolerance band associated with the advertisement and below an upper bound of the tolerance band associated with the advertisement. A second plurality of advertisements served on a performance basis that may be served in response to the advertisement delivery request is identified.

Abstract: A tolerance band is determined for an online advertisement campaign. The tolerance band defines upper and lower bounds on acceptable deviation from a cumulative linear advertisement delivery goal for the length of the campaign and may be employed to manage delivery of advertisement impressions during the campaign. The upper and lower bounds of tolerance band may flatten with time: acceptable deviation is generally higher at the beginning of the campaign and is lower as the campaign approaches its end date. The tolerance band may be employed to modify a periodically-determined delivery quota for an advertisement line based on the current performance of the advertisement line in relation to its tolerance band. An advertisement line that has fallen below the lower bound may get higher delivery priority relative to other advertisement lines so that it may be given more delivery opportunities.