Abstract: Embodiments facilitating data exploration in a computing environment by a processor. A multidimensional dataset may be received. The multidimensional dataset may be processed according to booting operation parameters. A visualization and exploration of an interactive representation of one or more probabilistic models using multidimensional dataset.

Abstract: Embodiments for providing enhanced data protection for storage systems in a computing environment by a processor. One or more queries received by a storage system may be identified. Approval or denial of transmission of data with the storage system may be regulated in relation to the one or more queries based a queried metadata and a plurality of rules and administrative policies.

Abstract: Embodiments facilitating data exploration in a computing environment by a processor. A multidimensional dataset may be received. The multidimensional dataset may be processed according to booting operation parameters. A visualization and exploration of an interactive representation of one or more probabilistic models for each one of a set of instances using the multidimensional dataset.

Abstract: Embodiments for analysis and summarization of current knowledge of data by a processor. A topic of a knowledge domain may be identified and extracted from one or more one or more data sources. A list of candidate subtopics, summaries, and a plurality of related data associated with the topic may be generated.

Abstract: Embodiments facilitating enhanced synergy between machine learning models and annotators in a computing environment by a processor. Annotation tasks may be coordinated between one or more annotators and machine learning models based on one or more annotator preferences and data annotation requirements of a machine learning model. The one or more annotator preferences and the data annotation requirements for coordinating the annotation tasks may be learned over a period of time.

Abstract: Embodiments facilitating data exploration in a computing environment by a processor. A multidimensional dataset may be received. The multidimensional dataset may be processed according to booting operation parameters. A visualization and exploration of an interactive representation of one or more probabilistic models for each one of a set of instances using the multidimensional dataset.

Abstract: Various embodiments are provided for providing intelligent library management in a computing environment by a processor. Application compatibility may be learned from a plurality of projects, repositories, application libraries, data sources, or a combination thereof. A list of recommended application libraries, ordered according to the application compatibility, may be automatically provided for implementation, integration, or replacements of one or more sections of an application library.

Abstract: In an approach to explaining probabilistic answers through contextualization, one or more computer processors receive a query associated with a probability value of a first event from a user. One or more computer processors parse the query into one or more constituent parts. Based on the one or more constituent parts, one or more computer processors determine the first event. One or more computer processors query a probability value of the first event, where the second event is similar to the first event. One or more computer processors determine the probability value of the first event and the probability value of the second event are known. One or more computer processors fetch the probability value of the first event and the probability value of the second event. One or more computer processors display the probability value of the first event and the probability value of the second event.

Abstract: A method, a computer system, and a computer program product for creating multiple models asynchronously is provided. Embodiments of the present invention may include receiving input data, wherein input data includes a full training dataset. Embodiments of the present invention may include building, asynchronously, one or more Bayesian network models using one or more portions of the input data on a first pipeline and building a free learning model using the full training dataset on a second pipeline. Embodiments of the present invention may include retrieving the one or more Bayesian network models from the first pipeline. Embodiments of the present invention may include retrieving the free learning model from the second pipeline.

Abstract: Various embodiments are provided for providing intelligent library management in a computing environment by a processor. Application compatibility may be learned from a plurality of projects, repositories, application libraries, data sources, or a combination thereof. A list of recommended application libraries, ordered according to the application compatibility, may be automatically provided for implementation, integration, or replacements of one or more sections of an application library.

Abstract: Embodiments for co-reference resolution and entity linking from unstructured text data by a processor. Semantic co-references and mentions of one or more entities may be resolved occurring in unstructured text data by linking the one or more entities using a domain knowledge ontology.

Abstract: Embodiments for discovery and analysis of interpersonal relationships from a collection of unstructured text data by a processor. A relationship between one or more entities and extracted text data from a plurality of unstructured text data may be identified such that the relationship includes a sentiment of the relationship, a type of relationship, temporal information, or a combination thereof. The one or more entities may be associated with a knowledge graph based on an ontology of concepts representing a domain knowledge. The extracted information and the identified relationship may be automatically aggregated into a multi-graph representation.

Abstract: Embodiments facilitating data exploration in a computing environment by a processor. A multidimensional dataset may be received. The multidimensional dataset may be processed according to booting operation parameters. A visualization and exploration of an interactive representation of one or more probabilistic models using multidimensional dataset.

Abstract: Embodiments for co-reference resolution and entity linking from unstructured text data by a processor. Semantic co-references and mentions of one or more entities may be resolved occurring in unstructured text data by linking the one or more entities using a domain knowledge ontology.

Abstract: Techniques that facilitate adaptive anonymization of data using statistical inference are provided. In one example, a system includes an anonymization component and a statistical learning component. The anonymization component applies an anonymization strategy to data associated with an electronic device. The statistical learning component modifies the anonymization strategy to generate an updated anonymization strategy for the data based on a machine learning process associated with a probabilistic model that represents the data.

Abstract: Embodiments for discovery and analysis of interpersonal relationships from a collection of unstructured text data by a processor. A relationship between one or more entities and extracted text data from a plurality of unstructured text data may be identified such that the relationship includes a sentiment of the relationship, a type of relationship, temporal information, or a combination thereof. The one or more entities may be associated with a knowledge graph based on an ontology of concepts representing a domain knowledge. The extracted information and the identified relationship may be automatically aggregated into a multi-graph representation.