Abstract: Facilitating of content entity annotation while maintaining joint quality, coverage and/or completeness performance conditions is provided. In one example, a non-transitory computer-readable medium comprises computer-readable instructions that, in response to execution, cause a computing system to perform operations. The operations include aggregating information indicative of initial entities for content and initial scores associated with the initial entities received from one or more content annotation sources and mapping the initial scores to respective values to generate calibrated scores. The operations include applying weights to the calibrated scores to generate weighted scores and combining the weighted scores using a linear aggregation model to generate a final score. The operations include determining whether to annotate the content with at least one of the initial entities based on a comparison of the final score and a defined threshold value.

Abstract: The present disclosure provides systems and methods for intervention optimization. A computing system obtain an entity history of each of a plurality of entities of a computer application. For each of the plurality of entities, the computing system can determine a respective probability that each of a plurality of available interventions will improve an objective value that is determined based at least in part on a measure of continued use of a computer application by the entity. The computing system can provide interventions of the plurality of available interventions to entities of the plurality of entities based at least in part on the respective probabilities determined via the machine-learned intervention selection model. Thus, a computing system can employ a machine-learned intervention selection model to select, on an entity-by-entity basis, interventions that are predicted to prevent the entity from churning out of the computer application.

Abstract: In a cooperative insight-sharing system, a method of reducing steps to index and retrieve an insight data object. The cooperative insight-sharing system stores the insight data object in an insight database, and compares insight attributes of the insight data object to known attributes stored in a reference database. Based on the comparison, the cooperative insight-sharing system derives an insight actionability measure, and links the insight actionability measure to the insight data object. The cooperative insight-sharing system generates a measure analysis of the insight actionability measure as a function of the reference database and the insight attributes of the insight data object, and causes an output device to render the measure analysis to a user.

Abstract: Facilitating of content entity annotation while maintaining joint quality, coverage and/or completeness performance conditions is provided. In one example, a non-transitory computer-readable medium comprises computer-readable instructions that, in response to execution, cause a computing system to perform operations. The operations include aggregating information indicative of initial entities for content and initial scores associated with the initial entities received from one or more content annotation sources and mapping the initial scores to respective values to generate calibrated scores. The operations include applying weights to the calibrated scores to generate weighted scores and combining the weighted scores using a linear aggregation model to generate a final score. The operations include determining whether to annotate the content with at least one of the initial entities based on a comparison of the final score and a defined threshold value.

Abstract: Facilitation of content entity annotation while maintaining joint quality, coverage and/or completeness performance conditions is provided. In one example, a system includes an aggregation component that aggregates signals indicative of initial entities for content and initial scores associated with the initial entities generated by one or more content annotation sources; and a mapping component that maps the initial scores to calibrated scores within a defined range. The system also includes a linear aggregation component that: applies selected weights to the calibrated scores, wherein the selected weights are based on joint performance conditions; and combines the weighted, calibrated scores based on a selected linear aggregation model of a plurality of linear aggregation models to generate a final score. The system also includes an annotation component that determines whether to annotate the content with one of the initial entities based on a comparison of the final score and a defined threshold value.

Abstract: A method of testing an application by variably adjusting parameters in executed instances of the application includes receiving data that represents two or more experiments, each experiment comprising at least one variation of values for one or more adjustable parameters in the application, assigning unique user identifiers (IDs) to users of the application, receiving, via a network, a request for parameter values from a computing device that is running an instance of the application, the request including a first user ID, determining whether the instance of the application is a participant in a variation group or a control group in each of the two or more experiments based on a function, per experiment, applied to the first user ID, and transmitting, to the computing device via the network, parameter values based on the participant determination.

Abstract: Systems and techniques are provided for a time series explorer. A request for time series including filter criteria may be received, a time series that is responsive to the request for time series may be determined by comparing event data for the time series stored in an event log to the filter criteria. The event data may include indications of an event that occurred in an application running on a computing device. A visual representation of the time series may be rendered. The visual representation of the time series may include a visual representation of an event indicated by the event data for the time series, and the visual representation of the time series may be transmitted to be displayed on a display.

Abstract: A resource context system (“context system”) computes a contextual profile for a resource based on selection data for the resource and contextual profiles of other resources that are identified as relevant to the resource. The contextual profile includes values that specify measures of relevance of the resource to each of a plurality of corresponding topics. The contextual profile is provided to a processing system, such as an advertisement management system or a search system that can identify topics for which the resource is relevant based on the contextual profile.

Abstract: A resource context system (“context system”) computes a contextual profile for a resource based on selection data for the resource and contextual profiles of other resources that are identified as relevant to the resource. The contextual profile includes values that specify measures of relevance of the resource to each of a plurality of corresponding topics. The contextual profile is provided to a processing system, such as an advertisement management system or a search system that can identify topics for which the resource is relevant based on the contextual profile.

Abstract: A container is provided having cushioning means which define at least in part a protected region for receiving an article such as a lap-top computer. The dimensions of the protected region are adjustable and the position of the cushioning means can be adjusted with the article in situ. The container can thereby actively provide the article with an optimised protected region which can confirm closely to articles of different sixes.

Abstract: Speaker identification is performed using a single Gaussian mixture model (GMM) for multiple speakers—referred to herein as a Discriminative Gaussian mixture model (DGMM). A likelihood sum of the single GMM is factored into two parts, one of which depends only on the Gaussian mixture model, and the other of which is a discriminative term. The discriminative term allows for the use of a binary classifier, such as a support vector machine (SVM). In one embodiment of the invention, a voice messaging system incorporates a DGMM to identify the speaker who generated a message, if that speaker is a member of a chosen list of target speakers, or to identify the speaker as a “non-target” otherwise.

Abstract: A method and apparatus is described for improving the efficiency of any machine that uses an algorithm that maps to a higher dimensional space in which a given set of vectors is used in a test phase. In particular, reduced set vectors are used. These reduced set vectors are different from the vectors in the set and are determined pursuant to an optimization approach other than the eigenvalue computation used for homogeneous quadratic kernels. An illustrative embodiment is described in the context of a support vector machine (SVM).

Abstract: A kernel-based method and apparatus includes a preprocessor, which operates on an input data in such a way as to provide invariance under some symmetry transformation.

Abstract: This invention modifies nearly any form of apparel, including baseball-style hats, by incorporating a portion of magnetic material into the article of apparel which allows for releasable attachment of a plurality of magnetic-based display panels.

Abstract: A method and system for forming an interpretation of an input expression, where the input expression is expressed in a medium, the interpretation is a sequence of symbols, and each symbol is a symbol in a known symbol set. In general, the system processes an acquired input data set representative of the input expression, to form a set of segments, which are then used to specify a set of consegmentations. Each consegmentation and each possible interpretation for the input expression is represented in a data structure. The data structure is graphically representable by a graph comprising a two-dimensional array of nodes arranged in rows and columns and selectively connected by directed arcs. Each path, extending through the nodes and along the directed arcs, represents one consegmentation and one possible interpretation for the input expression. All of the consegmentations and all of the possible interpretations for the input expression are represented by the set of paths extending through the graph.

Abstract: Noisy images of graphical or pictorial records, such as hand-written postal addresses, are cleaned by a method of analyzing the shapes of pixel clusters. According to such method, a set of structuring kernels is used to extract primitive shapes. The outcome of this extraction process is used to determine whether each pixel, in turn, is to be treated as part of a image element such as an alphanumeric character.