Groupon, Inc.

Bytedance Inc.

Abhaya Parthy

Amber Roy Chowdhury

Boris Lerner

Leopold Silberstein

Sri Subramaniam

Emma Sawin

Sunil Ramnik Raiyani

Changjian Zou

Raju Balakrishnan

Addhyan Pandey

Greyson Gregory

Ming-Chi Tsai

Lei Tang

Guokai Zeng

Ming-Jun Chen

An apparatus, method, and computer program product are provided to predict and model the performance of option data objects prior to the introduction of such option data objects into a network environment through the application of specific rule sets that are applied in a multi-stage arrangement on sets of extracted option data object parameters. In some example implementations, option data object parameters are extracted and parsed into sets of categorical and non-categorical parameters, which may be both quantitative and qualitative, and transmitted to one or more predictive models. Through the operation of the predictive models, the option data object parameters are transformed into a weighted value associated with the option data object that reflects a predicted performance level of the option data object and can be used when comparing multiple option data objects against each other.

Apparatus and method for option data object performance prediction and modeling

The present disclosure relates to inferring device rendered object interaction behavior. An apparatus is configured to receive historical device rendered object interaction data associated with a client device. The historical device rendered object interaction data includes a plurality of records. Each record is associated with a device rendered object category. For each record, the device rendered object category is extracted. For each device rendered object category, a penalty value is generated. The penalty value is a programmatically generated predicted network time delay during which device rendered objects associated with the device rendered object category are not to be transmitted to the client device. A penalty decision, used to determine whether to apply the penalty value to future transmissions of device rendered objects to the client device, is generated.

Method, apparatus, and computer program product for inferring device rendered object interaction behavior

An apparatus, method, and computer program product are provided to adjust and modify input signals used in connection with predictive models by detecting events, such as changes in operating parameters of data objects and/or related systems and calculating adjusted decay rates to be applied to time-series data associated with times prior to an occurrence of an event. In some example implementations, an indication of an event associated with a given datastream is received, in a manner which indicates the change in an operating parameter and the time at which the change occurred. Based at least in part on the indication of the event associated with the datastream, a second decay rate associated with the set of time-series data is determined and applied to the set of time-series data, such that an updated future performance level can be calculated by a predictive model.

Apparatus and method for forecasted performance level adjustment and modification

In general, embodiments of the present invention provide systems, methods and computer readable media for dynamically augmenting relevance rankings using data from external ratings sources.

Dynamic augmenting relevance rankings using data from external ratings sources

In general, embodiments of the present invention provide systems, methods and computer readable media for a universal relevance service framework for ranking and personalizing items.

Ranked relevance results using multi-feature scoring returned from a universal relevance service framework

Enforcing diversity in ranked relevance results returned from a universal relevance service framework

The present disclosure relates to inferring device rendered object interaction behavior. An apparatus is configured to receive historical device rendered object interaction data associated with a client device. The historical device rendered object interaction data includes a plurality of records. Each record is associated with an device rendered object category. For each record, the device rendered object category is extracted. For each device rendered object category, a penalty value is generated. The penalty value is a programmatically generated predicted network time delay during which device rendered objects associated with the device rendered object category are not to be transmitted to the client device. A penalty decision, used to determine whether to apply the penalty value to future transmissions of device rendered objects to the client device, is generated.

Growing community of inventors

Palo Alto, CA, United States of America

Abhaya Parthy