Abstract: Methods, systems, and computer program products for improving trustworthiness of artificial intelligence models in presence of anomalous data are provided herein. A method includes obtaining a machine learning model and a set of training data; determining one or more anomalous data points in said set of training data; for a given one of said anomalous data points, identifying attributes that decrease confidence with respect to at least one output of said machine learning model; determining that a root cause of said decreased confidence corresponds to one of: a class imbalance issue related to said at least one attribute, a confused class issue related to said at least one attribute, a low density issue related to said at least one attribute, and an adversarial issue related to said at least one attribute; and performing step(s) to improve said confidence based at least in part on said determined root cause.

Abstract: Methods, systems, and computer program products for domain aware explainable anomaly and drift detection for multi-variate raw data using a constraint repository are provided herein. A computer-implemented method includes obtaining a set of data and information indicative of a domain of said set of data; obtaining constraints from a domain-indexed constraint repository based on said set of data and said information, wherein the domain-indexed constraint repository comprises a knowledge graph having a plurality of nodes, wherein each node comprises an attribute associated with at least one of a plurality of domains and constraints corresponding to the attribute; detecting anomalies in said set of data based on whether portions of said set of data violate said retrieved constraints; generating an explanation corresponding to each of the anomalies that describe the attributes corresponding to the violated constraints; and outputting an indication of the anomalies and the corresponding explanation.

Abstract: Techniques for the automatic semantic analysis and comparison of chatbot capabilities are disclosed. A first chatbot specification associated with a first chatbot is obtained that includes a first plurality of characteristics arranged in a plurality of categories. A second chatbot specification associated with a second chatbot is obtained that includes a second plurality of characteristics arranged in the plurality of categories. One or more differences between the first plurality of characteristics and the second plurality of characteristics for each of the plurality of categories are identified based at least in part on the first plurality of characteristics and the second plurality of characteristics. A natural language expression corresponding to the identified one or more differences is generated and presented to a user via a graphical user interface.

Abstract: An approach is provided that detect a section of a document that is currently being read by a user on a display device as well as the user's current emotional state. In response to determining, based on the detected current emotional state, that reading assistance would be helpful to the user, the approach identifies terminology within the section of the document that is currently being read by the user, retrieves assistive texts related to the identified terminology, and provides the assistive texts to the user at the display screen.

Abstract: Methods, systems, and computer program products for improving trustworthiness of artificial intelligence models in presence of anomalous data are provided herein. A method includes obtaining a machine learning model and a set of training data; determining one or more anomalous data points in said set of training data; for a given one of said anomalous data points, identifying attributes that decrease confidence with respect to at least one output of said machine learning model; determining that a root cause of said decreased confidence corresponds to one of: a class imbalance issue related to said at least one attribute, a confused class issue related to said at least one attribute, a low density issue related to said at least one attribute, and an adversarial issue related to said at least one attribute; and performing step(s) to improve said confidence based at least in part on said determined root cause.

Abstract: Methods, systems, and computer program products for domain aware explainable anomaly and drift detection for multi-variate raw data using a constraint repository are provided herein. A computer-implemented method includes obtaining a set of data and information indicative of a domain of said set of data; obtaining constraints from a domain-indexed constraint repository based on said set of data and said information, wherein the domain-indexed constraint repository comprises a knowledge graph having a plurality of nodes, wherein each node comprises an attribute associated with at least one of a plurality of domains and constraints corresponding to the attribute; detecting anomalies in said set of data based on whether portions of said set of data violate said retrieved constraints; generating an explanation corresponding to each of the anomalies that describe the attributes corresponding to the violated constraints; and outputting an indication of the anomalies and the corresponding explanation.

Abstract: Techniques for the automatic semantic analysis and comparison of chatbot capabilities are disclosed. A first chatbot specification associated with a first chatbot is obtained that includes a first plurality of characteristics arranged in a plurality of categories. A second chatbot specification associated with a second chatbot is obtained that includes a second plurality of characteristics arranged in the plurality of categories. One or more differences between the first plurality of characteristics and the second plurality of characteristics for each of the plurality of categories are identified based at least in part on the first plurality of characteristics and the second plurality of characteristics. A natural language expression corresponding to the identified one or more differences is generated and presented to a user via a graphical user interface.

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: An approach is provided that detect a section of a document that is currently being read by a user on a display device as well as the user's current emotional state. In response to determining, based on the detected current emotional state, that reading assistance would be helpful to the user, the approach identifies terminology within the section of the document that is currently being read by the user, retrieves assistive texts related to the identified terminology, and provides the assistive texts to the user at the display screen.

Abstract: Methods and arrangements for document quality assessment. Documents are accepted and a quality specification containing predetermined quality criteria is assimilated. Each document is assessed based on the predetermined quality criteria, and a quality score is assigned to each document, the quality score being a function of positive and negative attributes assessed for each document.

Abstract: An arbitrary customer instance is transferred from a customer environment to a target managed-infrastructure-as-a-service cloud environment as a transferred image. An image adjustment plan, capturing at least one adjustment required to render the transferred image compliant with standards of the target managed-infrastructure-as-a-service cloud environment, is formulated. The image adjustment plan is executed to adjust the transferred image to obtain an adjusted image compliant with standards of the target managed-infrastructure-as-a-service cloud environment. The adjusted image is on-boarded into the managed-infrastructure-as-a-service cloud environment as a standard image thereof.

Abstract: Systems and associated methods for automated and semi-automated building of domain models for documents are described. Embodiments provide an approach to discover an information model by mining documentation about a particular domain captured in the documents. Embodiments classify the documents into one or more types corresponding to concepts using indicative words, identify candidate model elements (concepts) for document types, identify relationships both within and across document types, and consolidate and learn a global model for the domain.

Abstract: An arbitrary customer instance is transferred from a customer environment to a target managed-infrastructure-as-a-service cloud environment as a transferred image. An image adjustment plan, capturing at least one adjustment required to render the transferred image compliant with standards of the target managed-infrastructure-as-a-service cloud environment, is formulated. The image adjustment plan is executed to adjust the transferred image to obtain an adjusted image compliant with standards of the target managed-infrastructure-as-a-service cloud environment. The adjusted image is on-boarded into the managed-infrastructure-as-a-service cloud environment as a standard image thereof.

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: An arbitrary customer instance is transferred from a customer environment to a target managed-infrastructure-as-a-service cloud environment as a transferred image. An image adjustment plan, capturing at least one adjustment required to render the transferred image compliant with standards of the target managed-infrastructure-as-a-service cloud environment, is formulated. The image adjustment plan is executed to adjust the transferred image to obtain an adjusted image compliant with standards of the target managed-infrastructure-as-a-service cloud environment. The adjusted image is on-boarded into the managed-infrastructure-as-a-service cloud environment as a standard image thereof.

Abstract: Methods and arrangements for automatically finding the dependency of a software product on other software products or components. From an install image or directory, a signature is found by deriving the same from a directory structure of the software. Further, a directory tree structure is built and an approximate sub-tree matching algorithm is applied to find commonalities across software products.

Abstract: Methods and arrangements for automatically finding the dependency of a software product on other software products or components. From an install image or directory, a signature is found by deriving the same from a directory structure of the software. Further, a directory tree structure is built and an approximate sub-tree matching algorithm is applied to find commonalties across software products.

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: 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: Methods and arrangements for identifying a potential customer base of a concern. A contemplated method includes: identifying a prospective customer of a concern, via a social media network; identifying connections of the prospective customer within the social media network; determining a subset of the connections, wherein members of the subset comprise members of the concern; determining connections of the members of the subset; determining whether the connections of the members of the subset comprise the prospective customer; and if the connections of the members of the subset comprise the prospective customer, determining contact information of the prospective customer. Other variants and embodiments are broadly contemplated herein.