Abstract: Embodiments for semantic analysis of table content are provided. A document that includes a table portion and a non-table portion is received. A table result within the table portion of the document is identified. Contextual content associated with the table result is extracted from the non-table portion of the document. A data structure is generated for the table result. The data structure includes the table result and the contextual content associated with the table result.

Abstract: Various embodiments are provided for implementing an approximation nearest neighbour (ANN) search in a computing environment are provided. An approximation nearest neighbour (ANN) of a plurality of feature vectors in hyper-planes with dynamically variable subspaces by searching an inverted index may be retrieved.

Abstract: This method is a process that improves the execution time and maintains very precise clustering effectiveness utilizing a unique algorithm (identified as PPK means) that optimizes a process that is referred to as K-means clustering. The PPK means algorithm utilizes estimation values of signatures of new centroids for speed improvement and encoded data to provide a level of privacy protection. A system comprises a processor, operably coupled to memory, and that executes the computer-executable components, wherein the computer-executable components comprise: an encoding component that encodes a set of real-time valued vectors as bit vectors; and a clustering component that performs K-means clustering on the bit encoded vectors.

Abstract: Embodiments for extraction and summarization of decision discussions of a communication by a processor. The decision elements may be grouped together according to similar characteristics. The decision elements may be linked, and sentiments of the discussion participants towards each of the decision elements may be analyzed. A summary of the plurality of the decision elements may be provided via an interactive graphical user interface (GUI) on one or more Internet of Things (IoT) devices. The summary of the decision elements may be linked to domain knowledge. The summary may be enhanced using a domain knowledge.

Abstract: Embodiments for intelligent problem solving using visual input by a processor. An interactive dialog may be initiated using the one or more IoT computing devices for receiving one or more instructions, objectives, and the contextual information to define a selected task. Visual data and contextual information associated with the visual data may be collected from one or more Internet of Things (“IoT”) computing devices. One or more solutions may be for a selected task using the visual data and contextual data.

Abstract: Embodiments for extraction and summarization of decision discussions of a communication by a processor. The decision elements may be grouped together according to similar characteristics. The decision elements may be linked, and sentiments of the discussion participants towards each of the decision elements may be analyzed. A summary of the plurality of the decision elements may be provided via an interactive graphical user interface (GUI) on one or more Internet of Things (IoT) devices. The summary of the decision elements may be linked to domain knowledge. The summary may be enhanced using a domain knowledge.