Rovi Guides, Inc.

Adeia Guides Inc.

Samuel Meyer

Matthew Emans

Steven Bennett

Randall Kelley

Walter Richard Klappert

Systems and methods for performing fast-access playback operations are provided. A viewing history is stored that includes a plurality of play positions within a media asset that are associated with user interactions. A user request is received to perform a fast-access playback operation while accessing the media asset. While performing the fast-access playback operation at a first rate, it is determined whether a current fast-access playback position is within a threshold distance from a given one of the plurality of play positions stored in the viewing history. The fast-access playback operation is slowed down from the first rate to a second rate while the current fast-access playback position is within the threshold distance from the given play position.

Systems and methods for slowing down fast-access playback operations

Systems and methods are described herein for resolving advertisement placement conflicts. Specifically, a number of parameters may be entered into a system in order to distribute advertisements into advertisement slots. In many instances, a combination of these parameters causes a conflict in the system where all the parameters cannot be applied in order to place advertisements into advertisement slots. The conflict may be resolved by using an advertisement assignment model to determine which parameters may be relaxed in order to arrive at an optimal solution that violates a smallest number of parameters having the least priority. When such a solution is found, the advertisement assignment model may be modified and advertisements may be placed into advertisement slots based on the modified advertisement assignment model.

Systems and methods for resolving advertisement placement conflicts

Methods and systems are disclosed for an optimization system that recommends amounts of resources for use in reaching viewers during a media asset. The optimization system, using control circuitry, receives a user input of a first value of a resource and determines a first rate at which a number of unique household viewers reached during a first media asset changes for the first value. The optimization system compares the first rate to a threshold rate and determines whether the first rate equals or exceeds the threshold rate. The optimization system, in response to determining that the first rate does not equal or exceed the threshold rate, recommends a second value to the user.

Systems and methods for non-linear optimization of audience reach

Methods and systems for performing non-linear optimization of reach are described herein. The methods and systems may be used to compute the reach associated with different advertisement campaigns involving different combinations of spots. The method includes computing probabilities that a user will access a certain spot. The method includes retrieving a weight associated with the targeted user demographic. The method includes computing a first reach value using a first non-linear function, and a second reach value using a second non-linear function. The method includes comparing the two reach values to each other and to a predetermined reach threshold. The higher reach value larger than the predetermined reach threshold is selected and information associated with the selected reach value is provided to the user.

Methods and systems for performing non-linear reach optimization by computing reach values

Methods and systems are disclosed for using multiple reach optimization models together. These models may be used by an optimization system that helps an advertisement campaign manager decide how advertisements should be allocated between different media assets. In some embodiments, the models may be run simultaneously while their results and compared, and execution of some models may be ended based on the comparisons. In some embodiments, models may be combined together to create new models. In some embodiments, results from a first model may used as input in a second model running concurrently. In some embodiments, results from a previous execution of a model may be used to warm-start a subsequent execution of the model.

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Boston, MA, United States of America

Samuel Meyer