Abstract: A system, computer program product, and method are provided to leverage a taxonomy service to format ground truth data. An artificial intelligence platform processes ground truth data, including identification of one or more applicable taxonomy tags. The identified tags are filtered and applied to the ground truth data, thereby constructing an output string that incorporates the ground truth data together with one or more of the identified tags, effectively transforming the ground truth data. Application of the transformed ground truth data is employed to accurately identify the source and/or meaning of the natural language, and in one embodiment, to product a physical action or transformation of a physical hardware device.

Abstract: A system, computer program product, and method are provided to leverage a taxonomy service to format ground truth data. An artificial intelligence platform processes ground truth data, including identification of one or more applicable taxonomy tags. The identified tags are filtered and applied to the ground truth data, thereby constructing an output string that incorporates the ground truth data together with one or more of the identified tags, effectively transforming the ground truth data. Application of the transformed ground truth data is employed to accurately identify the source and/or meaning of the natural language, and in one embodiment, to product a physical action or transformation of a physical hardware device.

Abstract: A computer-implemented method according to one embodiment includes identifying a first classifier training data element and a second classifier training data element, calculating a similarity metric between the first classifier training data element and the second classifier training data element, and determining a classification for the first classifier training data element and the second classifier training data element, utilizing the similarity metric between the first classifier training data element and the second classifier training data element.

Abstract: Utilizing a computing device to provide professional skill recommendations for use in connection with a professional social network. A computing device receives an authorization for a service to monitor internet usage by a user. Determinations are made by the computing device of professional social networks the user is a member of, and a profession of the user. The service monitors search terms entered into websites and search engines by the user. The search terms are analyzed by the service executing on the computing device to determine search terms relevant to the profession of the user. A professional skill demonstrated by the search terms relevant to the profession of the user is determined. The service executing on the computing device generates professional skill recommendations for use with the professional social network based upon the professional skill demonstrated by the search terms relevant to the profession of the user.

Abstract: The disclosed embodiments include a computer-implemented method executed by a cognitive system. In one embodiment, the computer-implemented method includes the step of receiving a first image as part of a visual communication session. The method identifies metadata associated with the first image. The method identifies objects and their surroundings depicted in the first image. The method identifies properties associated with the objects and their surroundings depicted in the first image. The method retrieves information associated with the objects and their surroundings depicted in the first image based on the metadata and the properties associated with the objects and their surroundings. The method interacts with a user based in part on the information associated with the objects and their surroundings depicted in the first image.

Abstract: A mechanism is provided in a data processing system for comparing similarity of questioning answer system ground truth answers to question answering system result answers. The mechanism receives question answering system results. The question answering system results comprise questions posed to the question answering system, answers returned by the question answering system for each question posed to the question answering system, and a confidence value for each answer. The question answering system is trained or tested using the ground truth questions and answers. The mechanism performs a matching operation comparing each result answer in the question answering system results to a corresponding ground truth answer. The matching operation is an asymmetric containment comparison and wherein the matching operation determines similarity of each result answer to the corresponding ground truth answer. The mechanism determines whether each result answer is right or wrong based on results of the matching operation.

Abstract: In a multi-tiered simulation configuration, a combination of predictive models is executed such that each tier in the multi-tiered simulation configuration executes at least one predictive model to produce a corresponding set of predicted events, and a predicted event from a first tier in the configuration forms an input to a next tier in the configuration. Using a subset of a selected set of predicted events outputted from a corresponding selected tier in the multi-tiered simulation configuration, a set of features is extracted, each feature in the set of features having an effect on an outcome of the simulated process. The set of features is used in a demand level prediction model to predict a threshold demand, wherein reaching the threshold demand in an actual utilization of a computing resource is indicative of a likelihood of an unforeseen rise in a demand for the computing resource after a period.

Abstract: In a multi-tiered simulation configuration, a combination of predictive models is executed such that each tier in the multi-tiered simulation configuration executes at least one predictive model to produce a corresponding set of predicted events, and a predicted event from a first tier in the configuration forms an input to a next tier in the configuration. Using a subset of a selected set of predicted events outputted from a corresponding selected tier in the multi-tiered simulation configuration, a set of features is extracted, each feature in the set of features having an effect on an outcome of the simulated process. The set of features is used in a demand level prediction model to predict a threshold demand, wherein reaching the threshold demand in an actual utilization of a computing resource is indicative of a likelihood of an unforeseen rise in a demand for the computing resource after a period.

Abstract: A method, system, and computer program product for adjusting cloud resource allocation using n-tier simulation are provided in the illustrative embodiments. In a multi-tiered simulation configuration, a combination of predictive models is executed such that each tier executes at least one predictive model to produce a corresponding set of predicted events. Each tier simulates a process that is consuming a computing resource. Using a subset of a selected set of predicted events outputted from a corresponding selected tier, a set of features is extracted. each feature in the set of features has an effect on an outcome of the simulated process. The set of features is used in a demand level prediction model to predict a threshold demand. Reaching the threshold demand in an actual utilization of the computing resource is indicative of a likelihood of an unforeseen rise in a demand for the computing resource after a period.

Abstract: A mechanism is provided in a data processing system for assessing question answering system performance. The mechanism receives question answering system results. The question answering system results comprise questions posed to the question answering system, answers returned by the question answering system for each question posed to the question answering system, and a confidence value for each answer. The question answering system is trained or tested using the ground truth questions and answers. The mechanism performs a matching operation comparing each question in the question answering system results to questions in the ground truth. A given question is determined to be on-topic or off-topic based on results of the matching operation. For a plurality of confidence threshold values, the mechanism determines a rightness or wrongness of each answer in the question answering system results.

Abstract: A mechanism is provided in a data processing system for comparing similarity of questioning answer system ground truth answers to question answering system result answers. The mechanism receives question answering system results. The question answering system results comprise questions posed to the question answering system, answers returned by the question answering system for each question posed to the question answering system, and a confidence value for each answer. The question answering system is trained or tested using the ground truth questions and answers. The mechanism performs a matching operation comparing each result answer in the question answering system results to a corresponding ground truth answer. The matching operation is an asymmetric containment comparison and wherein the matching operation determines similarity of each result answer to the corresponding ground truth answer. The mechanism determines whether each result answer is right or wrong based on results of the matching operation.

Abstract: A method, system, and computer program product for adjusting cloud resource allocation using n-tier simulation are provided in the illustrative embodiments. In a multi-tiered simulation configuration, a combination of predictive models is executed such that each tier executes at least one predictive model to produce a corresponding set of predicted events. Each tier simulates a process that is consuming a computing resource. Using a subset of a selected set of predicted events outputted from a corresponding selected tier, a set of features is extracted. each feature in the set of features has an effect on an outcome of the simulated process. The set of features is used in a demand level prediction model to predict a threshold demand. Reaching the threshold demand in an actual utilization of the computing resource is indicative of a likelihood of an unforeseen rise in a demand for the computing resource after a period.

Abstract: An approach is provided to determine a horizontal scaling pattern for a workload. A production environment virtual machine (VM) is established in a cloud computing environment using a set of production operating characteristics. Mirrored environment VMs are also established in the cloud computing environment, with each of the mirrored environment VMs have adjusted operating characteristics as compared to the production environment VM. Requests are processed by the production and mirrored environment VMs with the processing time used being measured. The timing results corresponding to the production environment VM and to each of the mirrored environment VMs are compared and the set of production operating characteristics are adjusted based on comparison.