Oracle International Corporation

Webtrends Corporation

Accelerate Group Limited

Peter Crossley

Ethan William Dereszynski

Sean Jay McNamara

Dean C Kimball

Spencer Wood

Ryan Christopher Otis

A system for generating a topology of components based on a set of components provided by a user. The system identifies, for each particular component of the first set of components, one or more characteristics. The characteristics may include at least one of: a rule associated with the particular component, a requirement associated with the particular component, a data input type corresponding to the particular component, and data output type corresponding to the particular component. Based on the characteristics, the system determines that an additional component not included in the first set of components is required for connecting the first set of components. The system selects the additional component and determines a topology of components that includes the first set of components and the additional component. The system also determines a dataflow between components in the topology of components.

Semi-automated deployment for an intra-service communication infrastructure

The current document is directed to a query-as-a-service system ('QAAS system') that collects enormous volumes of data from network-connected entities, referred to as 'Things' in the phrase &#x201c;Internet of Things,&#x201d; persistently stores the collected data and provides a distributed-query-execution engine that allows remote clients to continuously execute queries against the collected data. In a described implementation, both the raw data and query results are persistently stored in the QAAS system, with the raw data stored for significantly longer periods of time. Query results generated by the query-processing engine are securely transmitted to QAAS remote clients for distribution to file systems, storage.

Query-as-a-service system that provides query-result data to remote clients

The current document is directed to a query-as-a-service system ('QAAS system') that collects enormous volumes of data from network-connected entities, referred to as 'Things' in the phrase &#x201c;Internet of Things,&#x201d; persistently stores the collected data and provides a distributed-query-execution engine that allows remote clients to continuously execute queries against the collected data. In a described implementation, both the raw data and query results are persistently stored in the QAAS system, with the raw data stored for significantly longer periods of time. Query results generated by the query-processing engine are securely transmitted to QAAS remote clients for distribution to file systems, storage appliances, applications, and other data sinks within client systems.

Methods and systems are provided for processing tag-based event communications using machine learning. One or more event communications are received from a user device. The communication(s) include key-value pairs representing an ordered sequence of multiple interaction events of a set of predefined events. Each communication of the one or more event communications includes one generated via execution of tag code integrated with code of an app page or of a webpage. A representation of the ordered sequence is processed using a machine learning model to generate one or more profile estimation results that include an identification of a particular user profile from amongst a set of stored user profile. Profile data is transmitted to a client system that identifies the particular user profile or is from the particular user profile.

Machine learning techniques for processing tag-based representations of sequential interaction events

The current document is directed to methods and systems for testing web sites. In certain implementations of the methods and systems, a testing service collects customer page-access and conversion information on behalf of a web site. The testing service is straightforwardly accessed and configured, through a web-site-based user interface, and is virtually incorporated into the web site by simple HTML-file modifications. A more efficient web-site-testing system nonuniformly distributes web-site accesses among web-page variants in order to more quickly and computationally efficiently determine a most effective web-page variant among a set of tested web-page variants. In certain implementations, nonuniform distribution of web-site accesses among web-page variants is facilitated by a Bayesian-inference method.

Method and system for web-site testing

The current application is directed to methods and systems for designing and configuring web-site testing and analysis. In certain implementations, a testing service collects customer page-access and conversion information on behalf of a web site. The testing service is straightforwardly accessed and configured, through a web-site-based graphical user interface, and is virtually incorporated into the web site.

Graphical-user-interface-based method and system for designing and configuring web-site testing and analysis

Embodiments of the present invention are directed to methods and systems for testing web sites and web servers. In discussed embodiments of the present invention, a third-party testing service collects page-access and conversion information on behalf of a web site. The third-party testing service is straightforwardly configured through a user interface and is engaged for real-time, live statistics collection by means of simple modifications of HTML files served or provided to users by a web site.

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Portland, OR, United States of America

Peter Crossley