Level 3 Communications, LLC

Genesys Telecommunications Laboratories, Inc.

Data.ai Inc.

App Annie Inc.

Solariat, Inc.

Other

Quorumlabs, Inc.

Paul Ernest Stolorz

Christopher T Dean

Jeffrey G Koller

Maksim Yevmenkin

Mark Brady

Michael S Warren

Jeffrey Eric Davitz

Ted Middleton

David Pfitzner

John K Salmon

Jackie Kellon Smith, Ii

Aric Hagberg

Jess Robert Kerlin

Eric Antoine MacKinnon

Marc Goroff

Tadaishi Yatabe Rodriguez

Abbie Marin Popa

Pang-Chieh Chen

An analytics system determines the number of downloads for a content item during a first time interval. The system receives engagement data from a plurality of client devices in a panel of client devices. Based on the engagement data, a partial install base for the content item during the first time interval is determined. Based on the determined partial install base for the content item and historical data for other content items, a preliminary install base for the content item during the first time interval is determined. Responsive to determining that the engagement for the content item is greater than a threshold value, an estimated number of downloads for the content item during the first time interval is determined. The estimated number of downloads for the content item during the first time interval is determined based on the preliminary install base for the content item for the first time interval.

Fast estimation of downloads for apps at launch

A system and a method are disclosed for recommending a set of actions to be performed to improve a target performance metric of a client application. An action recommendation system receives the target performance metric from a user associated with the client application. The action recommendation system determines features of the client application describing characteristics and performance history of the client application. The features of the client application and the target performance metric is provided as input to a machine learning model that outputs sets of target features that are likely to result in improvement for the target performance metric. The action recommendation system ranks the sets of target features and selects one of the sets based on the ranking. The action recommendation system determines a set of recommended actions based on the selected set of target features and presents the set of recommended actions to the user.

Using machine learning model to make action recommendation to improve performance of client application

A utility application for a mobile device inspects data packets from other mobile applications running on the device to gather and record usage data about those applications. Since users of the utility application may not reflect the true population for which the usage data is desired, a system de-biases the data reported from the utility applications using a machine learning model to predict demographics of the users of the utility application. To determine a training data set for the model, the system requests a user to provide a desired user attribute by way of an in-app questionnaire. This enables labeling utility usage data with the demographics, which can be weighted and extrapolated to determine usage across the population as a whole.

Determining usage data of mobile applications for a population

A network includes a first tier of servers, a second tier of servers and a third tier of servers. The first tier of servers comprises a plurality of primary servers capable of responding to requests. The plurality of primary servers includes at least one dynamic server having a load share characteristic that is dynamically altered during a first period in time and at least one static server having a constant load share characteristic during the first period in time. The second tier of servers includes at least two first layer overflow servers. Each of the first layer overflow servers is configured to provide response duties in the event that one or more of the primary servers is unavailable or overloaded. The third tier of servers comprising at least two second layer overflow servers. Each of the second layer overflow servers is configured to provide response duties in the event that one or more of the primary servers is unavailable or overloaded and one or more of the first layer overflow servers is unavailable or overloaded.

Multi-tiered server network

Content is inserted into conversations hosted on a takeoff site using creatives that provide lures and links to other material that users engaged in the conversation might find helpful and relevant. Such insertions are made in a contextually meaningful fashion through the use of a matching and decision process that determines best candidate creatives and an appropriate time and place for their insertion into the conversation.

Methods and apparatus for inserting content into conversations in on-line and digital environments

A method includes monitoring the operational status of at least some name servers in a name server network. Based on the monitoring, when an error or anomalous condition is detected at a particular name server, creating a policy to indicate the status of the particular name server. The policy is taken into account when resolving hostnames using the name server network.

Detecting anomalous conditions in a name server network

A method, operable in a framework wherein resources of a content provider may be delivered to clients from at least two distinct content delivery networks (CDNs). Responsive to a client request, one of the CDNs is selected, the selection being based at least in part on one or more policies set by the content provider. The client is provided with information associated with the selected CDN. The information may be a domain name such as a CNAME for the selected CDN. The policies may include a load share policy that specifies a relative load share for each CDN, and the selecting may attempt to satisfy the load share policy. Updated content provider policies may be obtained, at regular intervals.

Distributing requests across multiple content delivery networks based on subscriber policy

In a framework wherein resources of a content provider may be delivered to clients from different domains, a method distributes the requests based on content-provider policies. In some cases, the domains include at least two distinct content delivery network (CDN) domains. The domains may include a content provider domain. Responsive to a request, either the content provider domain or one of the two CDN domains is selected, the selection being based at least in part on one or more policies set by the content provider.

Policy-based content delivery network selection

There is disclosed apparatus and processes which address problems in the area of providing high availability and disaster recovery for computing systems and the data in them. These apparatus and processes can be used to provide high availability and disaster recovery for a computing system to be protected. The protected computing systems may be virtual computing systems.

Growing community of inventors

Los Altos, CA, United States of America

Paul Ernest Stolorz