Abstract: A hybrid linkage system may receive data records from different data sources, and may merge data records from the data sources with or without crisp or fuzzy constraints. The system may compute scores based on fuzzy match results between different data fields from a first data record and a second data record of a merged data record pair. The system may classify the merged data record pair with a weight from the first linguistic term based on the relative importance of the first fuzzy match score, and with a weight from the second linguistic term based on the relative importance of the second fuzzy match score, and may execute an action that uses consolidated data from the first and second data records in response to the first linguistic term and the second linguistic term evaluating to a match between the first data record and the second data record.

Abstract: A hybrid recommendation system may generate recommendations, predictions, and/or classifications by applying collaborative filtering to influence Convolutional Neural Networks (“CNNs”), Recurrent Neural Networks (“RNNs”), and/or other neural networks that model characteristic, structural, sequential, contextual, interactive, and/or other relationships from interactions of different users. The system may provide different user interactions as input to a first neural network, and the first neural network may model relationships between the different users and different items based on the interactions.

Abstract: A system may separate a transcript of a conversation into a first section corresponding to a first speaker in the conversation, and a second section corresponding to a second speaker in the conversation. The system may process, based on delimiters and punctuation marks, the first section and the second section to form a first speaker transcript and a second speaker transcript; determine, based on one or more topic models, a first set of key terms associated with the first speaker transcript and a second set of key terms associated with the second speaker transcript. The system may generate, based on a common set of key terms associated with the first set and the second of key terms, a first transcript summary of the first speaker transcript and a second transcript summary of the second speaker transcript; and generate a summary based on the first and the second transcript summaries.

Abstract: A system may separate a transcript of a conversation into a first section corresponding to a first speaker in the conversation, and a second section corresponding to a second speaker in the conversation. The system may process, based on delimiters and punctuation marks, the first section and the second section to form a first speaker transcript and a second speaker transcript; determine, based on one or more topic models, a first set of key terms associated with the first speaker transcript and a second set of key terms associated with the second speaker transcript. The system may generate, based on a common set of key terms associated with the first set and the second of key terms, a first transcript summary of the first speaker transcript and a second transcript summary of the second speaker transcript; and generate a summary based on the first and the second transcript summaries.

Abstract: A formal language for specifying and implementing multicast communication, named MSIL, comprises a set of constructs that are specific to multicast communication. The language provides semantic structures for repetitive, conditional, sequential, and parallel execution. It supports message passing, is extendible and domain independent. The language is flexible enough to be used for translating high-level multicasting requirements into abstractions, as well as implementing low-level systems supporting these requirements. MSIL can also be used as a command and communication language to control node behavior for multicast communication. The requirements, syntax and semantics of MSIL, together with the ontology for multicast communication are described. A selected set of high-level requirements, for multicast network management, is analyzed to determine the corresponding MSIL specifications.