Abstract: An embodiment includes identifying a tree type of vegetation depicted in an image. The embodiment segments that portion of the image using edge-detection processing resulting in a contour line that defines a tree perimeter. The embodiment detects that the tree is within a buffer distance from a power line. The embodiment determines the tree's species by comparing the contour line to candidate contour lines of different tree species and calculates a diameter of the tree's crown using the contour line. The embodiment estimates the tree's height using the species and the diameter of the crown. The embodiment calculates a risk value for the tree based on a risk of contact between the power line and the tree and issues a work order to maintain the tree to prevent contact with the power line.

Abstract: Mechanisms are provided to automatically generate a machine learning (ML) computer model. The mechanisms automatically generate a plurality of aggregated dataset groups, each having original dataset(s) grouped together based on a degree of correlation between characteristics of each of the original datasets. The mechanisms automatically generate, for each aggregated dataset group, a plurality of ML computer model instances, each being a ML computer model configured with a different combination of thresholds and hyperparameters than other ML computer model instances. The plurality of ML computer model instances are executed to generate performance metric information for each ML computer model instance. The performance metric information is analyzed to select a set of ML computer model instances for the aggregated dataset. The mechanisms select one or more ML computer model instances from across all of the sets of ML computer model instances as a candidate for deployment to a decision support computing system.

Abstract: A method for generating an output comprising one or more segments includes obtaining a plurality of profiles derived from unstructured data associated with a plurality of users, wherein a given one of the profiles corresponds to a respective one of the users; repetitively executing at least one machine learning technique on the plurality of profiles, each execution producing a respective set of one or more segments from the plurality of profiles; generating a complete graph by performing pairwise comparisons between sets of segments from respective executions; applying at least one persistency graph algorithm to the complete graph to find one or more coherent clusters comprising one or more segments that are persistent across the repetitive executions of the machine learning technique; and producing the output at least in part by selecting at least one of the segments from at least one of the coherent clusters.

Abstract: A method for generating an output comprising one or more segments includes obtaining a plurality of profiles derived from unstructured data associated with a plurality of users, wherein a given one of the profiles corresponds to a respective one of the users; repetitively executing at least one machine learning technique on the plurality of profiles, each execution producing a respective set of one or more segments from the plurality of profiles; generating a complete graph by performing pairwise comparisons between sets of segments from respective executions; applying at least one persistency graph algorithm to the complete graph to find one or more coherent clusters comprising one or more segments that are persistent across the repetitive executions of the machine learning technique; and producing the output at least in part by selecting at least one of the segments from at least one of the coherent clusters.

Abstract: A method for generating an output comprising one or more segments includes obtaining a plurality of profiles derived from unstructured data associated with a plurality of users, wherein a given one of the profiles corresponds to a respective one of the users; repetitively executing at least one machine learning technique on the plurality of profiles, each execution producing a respective set of one or more segments from the plurality of profiles; generating a complete graph by performing pairwise comparisons between sets of segments from respective executions; applying at least one persistency graph algorithm to the complete graph to find one or more coherent clusters comprising one or more segments that are persistent across the repetitive executions of the machine learning technique; and producing the output at least in part by selecting at least one of the segments from at least one of the coherent clusters.

Abstract: A method for generating an output comprising one or more segments includes obtaining a plurality of profiles derived from unstructured data associated with a plurality of users, wherein a given one of the profiles corresponds to a respective one of the users; repetitively executing at least one machine learning technique on the plurality of profiles, each execution producing a respective set of one or more segments from the plurality of profiles; generating a complete graph by performing pairwise comparisons between sets of segments from respective executions; applying at least one persistency graph algorithm to the complete graph to find one or more coherent clusters comprising one or more segments that are persistent across the repetitive executions of the machine learning technique; and producing the output at least in part by selecting at least one of the segments from at least one of the coherent clusters.

Abstract: Embodiments include method, systems and computer program products for inferring user demographic groups through categorization of social media data. Aspects include receiving, by a processor, unknown user data made up of social media data and social media metadata for an unknown user. Also, aspects include analyzing the unknown user data to determine features of the unknown user data that indicate the unknown user belongs to a demographic group. Next, aspects include analyzing, via a machine learning algorithm, the features of the unknown user data to determine a confidence level for the unknown user belonging to each demographic group and updating a user demographics database based upon the confidence level for the unknown user belonging to each demographic group.

Abstract: A set of current and historical electronic activity data are received from a customer. The activity data corresponds to the customer's interaction with an electronic product entry within a store. One or more electronic activities can be associated with one or more predetermined seller objectives. The seller's objectives are based on maximizing financial profit and minimizing cost of reward distribution. A reward score value is assigned to a customer based on an association between one or more of the customer's electronic activities and one or more of the predetermined seller objectives. A reward is selected based on the reward score wherein the rewards are also associated with one or more of the predetermined seller objectives, also based on the reward score value. The selected reward associated with the calculated reward score is communicated to the customer.

Abstract: Techniques are presented for providing a software fitting assessment. The techniques may be performed by methods, apparatus, and/or computer program products. The techniques include automatically matching on a computer system one or more specified requirements for a project with one or more software functions stored in a repository. The automatically matching includes mining the repository in order to match requirements. The repository includes software functions, requirements accumulated from previous projects, and results of stored matches between the software functions and the requirements accumulated from previous projects. The techniques include outputting by the computer system one or more results of the matching.

Abstract: Systems and techniques for generating recommendations for items likely to be of interest to a user. Upon an indication that a recommendation may be needed by a user, a plurality of recommendations from different sources are generated and combined. Suitably, each recommendation includes parameters such as accuracy and confidence parameters. Combining the recommendations comprises adjusting the parameters based on a set of rules established by an operator of a system for combining recommendations. The rules may be adjusted by operator inputs through an interface and may be adjusted, if desired, during generation of a recommendation. At least one of the recommendation sources generates recommendations based on social grouping, wherein social groupings are identified based on connections between members and similarity of purchased between members, and wherein a recommendation for a specific user is generated by identifying groups to which the user belongs and items popular within such groups.

Abstract: A method for identifying influence on user interest for products and ability of users and products to be influenced is disclosed. A processor identifies a degree of influence a number of influencers has over user interest for each of a number of products based on a history of user interest of a number of users for the number of products, wherein each influencer in the number of influencers as one of a user in the number of users and a product in the number of products. The processor also identifies a degree of ability of one or more of the number of users and the number of products to be influenced based on the degree of influence of each of the number of influencers and a number of relationships between the one or more of the number of users and the number of products and the number of influencers.

Abstract: Aspects of the invention provide a method for making a product substitution recommendation to a consumer. Initially, a rejection of the product by the consumer is detected. The rejection comprises a failure to purchase a product after the product is added to an online shopping cart, or a return of a product after the product is purchased. Subsequently, a reason for the rejection is determined. A recommendation for a substitute product is then formulated at least in part based on the determined reason for the rejection. Lastly, the recommendation for the substitute product is presented to the consumer.

Abstract: A method (and system) of modeling runtime behavior for a software application includes limiting a portion of a run to be analyzed using criteria that define an analysis scenario, structuring events of the analysis scenario as a flow of logical content through a plurality of transformations, applying labels to elements of the flow, and generating a behavior signature for the analysis scenario based on the labels.

Abstract: Techniques are presented for providing a software fitting assessment. The techniques may be performed by methods, apparatus, and/or computer program products. The techniques include automatically matching on a computer system one or more specified requirements for a project with one or more software functions stored in a repository. The automatically matching includes mining the repository in order to match requirements. The repository includes software functions, requirements accumulated from previous projects, and results of stored matches between the software functions and the requirements accumulated from previous projects. The techniques include outputting by the computer system one or more results of the matching.

Abstract: Techniques are presented for providing a software fitting assessment. The techniques may be performed by methods, apparatus, and/or computer program products. The techniques include automatically matching on a computer system one or more specified requirements for a project with one or more software functions stored in a repository. The automatically matching includes mining the repository in order to match requirements. The repository includes software functions, requirements accumulated from previous projects, and results of stored matches between the software functions and the requirements accumulated from previous projects. The techniques include outputting by the computer system one or more results of the matching.

Abstract: The present invention discloses a software development tool that includes a model development interface, an aspect design tool, and a model transformation engine. The model development interface can permit a developer to graphically design at least one software model. The aspect design tool for the model development interface can be configured to permit a user to specify at least one aspect to be applied to a model of the model development interface. The model transformation engine can transform a model of the model development interface having at least one aspect defined via the aspect design tool into automatically generated aspect code integrated with base language code.

Abstract: A process of analyzing performance of a computer program including a plurality of components includes steps of: receiving a call tree profile having a plurality of nodes, each node representing an invocation and each node being annotated with a cumulative performance cost for the node; a set of one or more components of interest to a user; and a threshold level of a cumulative performance cost associated with invocations of methods of the component that constitutes an expensive method invocation; analyzing the call tree profile from leaf nodes, the analyzing step comprising selecting a set of one or more components of interest to a user and selecting only invocations that exceed the threshold level, and pruning the set of invocations that are not selected. Finally the process includes a step of presenting to the user a list of costs associated with the selected invocations.

Abstract: The present invention discloses a software development tool that includes a model development interface, an aspect design tool, and a model transformation engine. The model development interface can permit a developer to graphically design at least one software model. The aspect design tool for the model development interface can be configured to permit a user to specify at least one aspect to be applied to a model of the model development interface. The model transformation engine can transform a model of the model development interface having at least one aspect defined via the aspect design tool into automatically generated aspect code integrated with base language code.

Abstract: A method (and system) of modeling runtime behavior for a software application includes limiting a portion of a run to be analyzed using criteria that define an analysis scenario, structuring events of the analysis scenario as a flow of logical content through a plurality of transformations, applying labels to elements of the flow, and generating a behavior signature for the analysis scenario based on the labels.

Abstract: A process of analyzing performance of a computer program including a plurality of components, each component comprising a plurality of methods, the program being executable by carrying out a plurality of calling sequences, each calling sequence includes a plurality of invocations of the methods, the process includes steps of: receiving a call tree profile having a plurality of nodes, each node representing an invocation and each node being annotated with a cumulative performance cost for the node; a set of one or more components of interest to a user; and a threshold level of a cumulative performance cost associated with invocations of methods of the component that constitutes an expensive method invocation; analyzing the call tree profile from leaf nodes, the analyzing step comprising selecting a set of one or more components of interest to a user and selecting only invocations that exceed the threshold level, and pruning the set of invocations that are not selected.