Abstract: One embodiment provides a method, including: identifying at least one protected attribute of a task of annotating information, wherein the task is assigned to at least one crowdsourced worker for performance of the task; generating at least one question for detecting bias of the at least one crowdsourced worker with respect to the at least one protected attribute, the at least one question comprising a previously provided annotation; providing the at least one question to the at least one crowdsourced worker at a period during performance of the task; computing a bias of the at least one crowdsourced worker with respect to the at least one protected attribute by comparing (i) an annotation provided by the crowdsourced worker to the at least one question and (ii) the previously provided annotation; and updating a profile of the at least one crowdsourced worker with the computed bias.

Abstract: Methods, systems, and computer program products for generating a framework for prioritizing machine learning model offerings via a platform are provided herein. A computer-implemented method includes processing, via a computing platform, a machine learning model input by a first user and metadata corresponding to the machine learning model input by the first user; automatically comparing, via the computing platform, the metadata corresponding to the machine learning model with metadata corresponding to one or more existing machine learning models stored by the computing platform; automatically calculating, via the computing platform, initial pricing information for the machine learning model based on the comparison; and outputting, via an interactive user interface of the computing platform, the machine learning model to one or more additional users for purchase in accordance with the calculated initial pricing information.

Abstract: One embodiment provides a method, including: receiving, from a user, (i) a dataset and (ii) an intended output from the dataset that is generated in view of a given analytical framework for the dataset, wherein the intended output identifies an output that the user wants from the dataset and wherein the dataset is related to an analytical domain; identifying a plurality of dataset functions related to the analytical domain; determining one or more dataset functions for each of one or more operations identified, wherein the one or more operations are identified using the repository to identify operations used to result in an intended output similar to the received intended output; and recommending an ordered subset of the one or more dataset functions to be used to transform the dataset to the intended output, wherein the ordered subset comprises (i) one dataset function for each of the one or more operations and (ii) an order for performing the one or more operations.

Abstract: A method for capturing evolving data, comprising observing a data graph, identifying a first entity within the graph, defining a first property of the first entity, and identifying a first data value corresponding to the property and the entity. The method further comprises associating a second entity with the first entity at first data value, and forming a dimension of the first entity with associations to other entities within the graph for different data values of the first property. Identifying the first entity comprises identifying a property of the first entity representing a dimension but the property does not relate to other entities through the dimension. Defining the first property comprises identifying an attribute of the first entity that will not change; establishing the attribute as the first property.

Abstract: The present subject matter relates to migrating a virtual machine (VM) from a source server to a destination server. The migration involves computation of a suitability score for each particular server in the plurality of candidate servers. The suitability score for a server indicates the suitability of the server to host the VM. In an example implementation, the suitability score for a server is computed based on satisfaction of at least one criterion for operation of the VM by the server.

Abstract: Methods, systems, and computer program products for assessing value of one or more data sets in the context of a set of applications are provided herein. A computer-implemented method includes selecting analytic applications of interest based on a characterization of data attributes of each of the available data sets; automatically determining an impact of each of the data attributes of each of the available data sets on an end value of each of the analytic applications of interest; automatically computing an amount of improvement to the end value of each of the analytic applications of interest based on inclusion of an additional data set; and automatically determining a value attributed to the additional data set based on a comparison of (i) the cost of adding the additional data set to the available data sets to (ii) the computed amount of improvement based on the inclusion of the additional data set.

Abstract: Examples include bypassing a portion of an analytics workflow. In some examples, execution of an analytics workflow may be monitored upon receipt of a raw data and the execution may be interrupted at an optimal bypass stage to obtain insights data from the raw data. A similarity analysis may be performed to compare the insights data to a stored insights data in an insights data repository. Based, at least in part, on a determination of similarity, a bypass operation may be performed to bypass a remainder of the analytics workflow.

Abstract: Systems and methods for resource identification. Preferably, this can be undertaken via modeling in which primary constraints include requirements and availability and building a resource map that includes alternatives which can help in the realization of the function.

Abstract: Embodiments of the invention provide systems, methods and computer program products for optimizing cloud service delivery within a cloud computing environment. A cloud service request (CSR) is received from a cloud customer in the cloud computing environment, the CSR comprising at least one parameter of one or more existing cloud services accessed by the cloud customer that are provided by one or more existing cloud service providers. At least one parameter of the CSR is monitored in a cloud service registry comprising a plurality of cloud services provided by a plurality of cloud service providers and one or more parameters corresponding to each cloud service of the plurality of cloud services. Based on the monitoring, a new cloud service provider is determined who may provide a better cloud service with respect to the at least one parameter in the CSR being monitored.

Abstract: A method for capturing evolving data, comprising observing a data graph, identifying a first entity within the graph, defining a first property of the first entity, and identifying a first data value corresponding to the property and the entity. The method further comprises associating a second entity with the first entity at first data value, and forming a dimension of the first entity with associations to other entities within the graph for different data values of the first property. Identifying the first entity comprises identifying a property of the first entity representing a dimension but the property does not relate to other entities through the dimension. Defining the first property comprises identifying an attribute of the first entity that will not change; establishing the attribute as the first property.

Abstract: Methods, systems, and computer program products for identifying marginal-influence maximizing nodes in networks are provided herein. A method includes determining, across a network comprising multiple nodes, one or more target nodes in relation to a query node, wherein said determining comprises calculating a matching score for each of the multiple nodes based on attributes identified in a query associated with the query node; computing a probability associated with each edge in the network that connects two or more of the multiple nodes, wherein the probability comprises the likelihood, given the attributes identified in the query, that a given node is to forward information to a node connected thereto via a given edge; and identifying at least one path from the query node to at least one of the target nodes based on the computed probability associated with each edge in the network.

Abstract: Methods and systems of defining product attributes may involve receiving a search query and extracting a user expectation from the search query. In addition, an attribute may be defined for a product based on the user expectation. In one example, consumer generated content such as forum content, review content, blog content and social networking content, is used to define the attribute.

Abstract: The present subject matter relates to migrating a virtual machine (VM) from a source server to a destination server. The migration involves computation of a suitability score for each particular server in the plurality of candidate servers. The suitability score for a server indicates the suitability of the server to host the VM. In an example implementation, the suitability score for a server is computed based on satisfaction of at least one criterion for operation of the VM by the server.

Abstract: Methods, systems, and articles of manufacture for generating a multi-dimensional social network identifier are provided herein. A method includes capturing one or more items of web information pertaining to past activity associated with a given individual; determining one or more user metrics associated with the given individual based on the one or more items of web information; quantifying a measure of similarity of the one or more user metrics associated with the given individual and the one or more user metrics associated with one or more additional individuals; and generating an identifier for the given individual based on the measure of similarity, and wherein said identifier differs from identification information attributable to the given individual on a social network.

Abstract: Some examples relate to associating an insight with data. In an example, data may be received. A determination may be made that data type of the data is same as compared to an earlier data. An insight generated from the earlier data may be identified, wherein the insight may represent intermediate or resultant data generated upon processing of the earlier data by an analytics function, and wherein during generation metadata is associated with the insight. An analytics function used for generating the insight may be identified.

Abstract: Methods, systems, and computer program products for assessing value of one or more data sets in the context of a set of applications are provided herein. A computer-implemented method includes selecting analytic applications of interest based on a characterization of data attributes of each of the available data sets; automatically determining an impact of each of the data attributes of each of the available data sets on an end value of each of the analytic applications of interest; automatically computing an amount of improvement to the end value of each of the analytic applications of interest based on inclusion of an additional data set; and automatically determining a value attributed to the additional data set based on a comparison of (i) the cost of adding the additional data set to the available data sets to (ii) the computed amount of improvement based on the inclusion of the additional data set.

Abstract: Methods, systems, and computer program products for identifying marginal-influence maximizing nodes in networks are provided herein. A method includes determining, across a network comprising multiple nodes, one or more target nodes in relation to a query node, wherein said determining comprises calculating a matching score for each of the multiple nodes based on attributes identified in a query associated with the query node; computing a probability associated with each edge in the network that connects two or more of the multiple nodes, wherein the probability comprises the likelihood, given the attributes identified in the query, that a given node is to forward information to a node connected thereto via a given edge; and identifying at least one path from the query node to at least one of the target nodes based on the computed probability associated with each edge in the network.

Abstract: Methods and arrangements for reconfiguring an analytics model without retraining the analytics model. A contemplated method includes: providing a cloud-based classifier which performs analytics on input data, the classifier including an analytics model; receiving a first data set at the classifier, wherein the first data set is a training data set; via the analytics model, discovering features in the first data set; receiving a second input data set at the classifier; via the analytics model, discovering one or more new features in the second input data set; and reconfiguring the analytics model, without retraining the analytics model, based on one or more new features discovered in the second input data set. Other variants and embodiments are broadly contemplated herein.

Abstract: A system for injecting business content dynamically based on the context of the user. A media content analysis tool may be used to analyze existing media to identify features and insert tags based on the content and/or time. A media content orchestrator may be used to author scriplets containing product advice for the media stream to insert and associate scriplets to tags in the media stream. The media player, equipped with a codec for the new media format, performs functions such as browsing product information, places orders, or the like.

Abstract: Methods and arrangements for reconfiguring an analytics model without retraining the analytics model. A contemplated method includes: providing a cloud-based classifier which performs analytics on input data, the classifier including an analytics model; receiving a first data set at the classifier, wherein the first data set is a training data set; via the analytics model, discovering features in the first data set; receiving a second input data set at the classifier; via the analytics model, discovering one or more new features in the second input data set; and reconfiguring the analytics model, without retraining the analytics model, based on one or more new features discovered in the second input data set. Other variants and embodiments are broadly contemplated herein.