Abstract: A method, apparatus and computer program product for establishing a logical connection between an indirect utterance and a transaction is described. An indirect utterance is received from a user as an input to a conversational system. The indirect utterance is parsed to a first logical form. A first set of predicates and terms is mapped from the first logical form to a first subgraph in a knowledge graph. A second set of predicates and terms is mapped from a second logical form belonging to a transaction to a second subgraph of the knowledge graph. A best path in the knowledge graph between the first subgraph and the second subgraph is searched for while transforming the first logical form using the node and edge labels along the best path to generate an intermediate logical form. A system action is performed for a transaction if a graph structure of the intermediate logical form matches the graph structure of the logical form of the transaction above a threshold.

Abstract: Systems and techniques that facilitate spurious relationship filtration from external knowledge graphs based on distributional semantics of an input corpus are provided. In one or more embodiments, a context component can generate a context-based word embedding of one or more first terms in a document collection. The embedding can yield vector representations of the one or more first terms. The one or more first terms can correspond to knowledge terms in one or more first nodes of a knowledge graph. In one or more embodiments, a filtering component can filter out a relationship between the one or more first nodes and a second node of the knowledge graph based on a similarity value being less than a threshold. The similarity value can be a function of the vector representations of the one or more first terms. In various embodiments, cosine similarity can be used to compute the similarity value.

Abstract: Organizing and/or aligning fragments of text that are included in a set of physical and/or digital documents so that the arrangement of the text fragments is in a readily understandable and meaningful format for a given reader. This organization and/or alignment uses a relation model of the various text fragments to correlate a meaning between and amongst the various text fragments to ultimately determine the final alignment and/or arrangement of those text fragments.

Abstract: A first neural network is operated on a processor and a memory to encode a first natural language string into a first sentence encoding including a set of word encodings. Using a word-based attention mechanism with a context vector, a weight value for a word encoding within the first sentence encoding is adjusted to form an adjusted first sentence encoding. Using a sentence-based attention mechanism, a first relationship encoding corresponding to the adjusted first sentence encoding is determined. An absolute difference between the first relationship encoding and a second relationship encoding is computed. Using a multi-layer perceptron, a degree of analogical similarity between the first relationship encoding and a second relationship encoding is determined.

Abstract: A computer-implemented method for performing cross-document coreference for a corpus of input documents includes determining mentions by parsing the input documents. Each mention includes a first vector for spelling data and a second vector for context data. A hierarchical tree data structure is created by generating several leaf nodes corresponding to respective mentions. Further, for each node, a similarity score is computed based on the first and second vectors of each node. The hierarchical tree is populated iteratively until a root node is created. Each iteration includes merging two nodes that have the highest similarity scores and creating an entity node instead at a hierarchical level that is above the two nodes being merged. Further, each iteration includes computing the similarity score for the entity node. The nodes with the similarity scores above a predetermined value are entities for which coreference has been performed in input documents.

Abstract: A policy violation detection computer-implemented method, system, and computer program product, includes predicting a violation of a portion of a policy by a future action and delivering an alert of the violation to a user device, alert settings for privacy are toggled on the user device based on a user profile.

Abstract: A computer-implemented method according to one embodiment includes converting an input question into a vector form using trained word embeddings; constructing a type similarity matrix using a predetermined ontology; and determining a score for all possible types for the input question, based on the input question in vector form and the type similarity matrix.

Abstract: Training a machine learning model such as a neural network, which can automatically extract a hypernym from unstructured data, is disclosed. A preliminary candidate list of hyponym-hypernym pairs can be parsed from the corpus. A preliminary super-term—sub-term glossary can be generated from the corpus, the preliminary super-term—sub-term glossary containing one or more super-term—sub-term pairs. A super-term—sub-term pair can be filtered from the preliminary super-term—sub-term glossary, responsive to detecting that the super-term—sub-term pair is not a candidate for hyponym-hypernym pair, to generate a final super-term—sub-term glossary. The preliminary candidate list of hyponym-hypernym pairs and the final super-term—sub-term glossary can be combined to generate a final list of hyponym-hypernym pairs. An artificial neural network can be trained using the final list of hyponym-hypernym pairs as a training data set, the artificial neural network trained to identify a hypernym given new text data.

Abstract: A policy violation detection computer-implemented method, system, and computer program product, includes extracting a policy activity from a policy, the policy activity including an actor in the policy, an object of the policy, an action of the policy, and policy scope metadata, capturing a transaction by a user including metadata of the transaction, translating the transaction by the user into an actor in the transaction, an action of the transaction, and an object of the transaction, and alerting the user of a policy violation by navigating a knowledge graph is-a hierarchy to relate the actor in the transaction to the actor in the policy, the object of the transaction to an object of the policy, and the action of the transaction to an action of the policy activity.

Abstract: A computer-implemented method identifies one or more concepts from a document, wherein the document comprises information on completing a task. The method computes a relevance value of an utterance with respect to completing the task using the one or more identified concepts. The method removes the utterance from a dialog model to be used for completing the task when the relevance value of the utterance is below a given threshold value.

Abstract: Organizing and/or aligning fragments of text that are included in a set of physical and/or digital documents so that the arrangement of the text fragments is in a readily understandable and meaningful format for a given reader. This organization and/or alignment uses a relation model of the various text fragments to correlate a meaning between and amongst the various text fragments to ultimately determine the final alignment and/or arrangement of those text fragments.

Abstract: Entities and relations associated with source code of a program are extracted. An entity completion on the extracted entities and relationships is performed to produce a knowledge graph of the source code. Repeated patterns of relationships are identified from the knowledge graph across the source code.

Abstract: A method, a computer program product, and a computer system determine when to transfer a communication session from an agent to a bot. The method includes monitoring the communication session between the agent and a user. The method includes determining a continuing utility value indicating a predicted continuing cost to maintaining the communication session with the agent. The continuing utility value is indicative of a predicted continuing benefit to maintaining the communication with the agent. The method includes determining a transferring utility value indicating a predicted transferring cost to transferring the communication session from the agent to the bot. The transferring utility value is indicative of a predicted transferring benefit to transferring the communication session from the agent to the bot. The method includes, as a result of the predicted transferring benefit being greater than the predicted continuing benefit, transferring the communication session from the agent to the bot.

Abstract: An autonomous vehicle utilizing machine learning method, system, and computer program product include training, by a computing device, a driver attention model utilizing historical ambient sensor data and historical physiological sensor data associated with an autonomous vehicle, receiving ambient sensor data associated with a currently driving autonomous vehicle, receiving physiological sensor data associated with a driver of the currently driving autonomous vehicle, and using, by a computing device, the trained driver attention model in conjunction with the ambient sensor data and the physiological sensor data to generate an alert for a driver of the currently driving autonomous vehicle.

Abstract: A query-focused faceted structure generation method, system, and computer program product for generating a query-focused faceted structure from a taxonomy for searching a document collection, including ingesting a document corpus, generating a vector space representation of a query and instances from a taxonomy of the document corpus, and producing a dynamic structure of a relevant facet categories and facet values using a two-vector space representation from the generated vector space representation.

Abstract: Embodiments include methods, systems, and computer program products for detection and remediation of anxiety. Aspects include receiving an anxiety indicator. Aspects also include analyzing the anxiety indicator to determine whether an anxiety level exceeds an anxiety threshold. Aspects also include, based upon a determination that the anxiety level exceeds the anxiety threshold, selecting a first sound. Aspects also include outputting the first sound. Aspects also include receiving an anxiety feedback. Aspects also include determining, based upon the anxiety feedback, whether the anxiety level is decreasing.

Abstract: A processor may record a first location at an event with at least one person. The processor may monitor a plurality of actions of that at least one person at the first location. The processor may interpret at least one action of the at least one person that indicates a change of interest to a second location at the event. Based on the at least one action, the processor may determine the second location at the event. The processor may record the second location at the event.

Abstract: A computer-implemented method identifies one or more concepts from a document, wherein the document comprises information on completing a task. The method computes a relevance value of an utterance with respect to completing the task using the one or more identified concepts. The method removes the utterance from a dialog model to be used for completing the task when the relevance value of the utterance is below a given threshold value.

Abstract: A computer-implemented method for performing cross-document coreference for a corpus of input documents includes determining mentions by parsing the input documents. Each mention includes a first vector for spelling data and a second vector for context data. A hierarchical tree data structure is created by generating several leaf nodes corresponding to respective mentions. Further, for each node, a similarity score is computed based on the first and second vectors of each node. The hierarchical tree is populated iteratively until a root node is created. Each iteration includes merging two nodes that have the highest similarity scores and creating an entity node instead at a hierarchical level that is above the two nodes being merged. Further, each iteration includes computing the similarity score for the entity node. The nodes with the similarity scores above a predetermined value are entities for which coreference has been performed in input documents.

Abstract: Systems and techniques that facilitate spurious relationship filtration from external knowledge graphs based on distributional semantics of an input corpus are provided. In one or more embodiments, a context component can generate a context-based word embedding of one or more first terms in a document collection. The embedding can yield vector representations of the one or more first terms. The one or more first terms can correspond to knowledge terms in one or more first nodes of a knowledge graph. In one or more embodiments, a filtering component can filter out a relationship between the one or more first nodes and a second node of the knowledge graph based on a similarity value being less than a threshold. The similarity value can be a function of the vector representations of the one or more first terms. In various embodiments, cosine similarity can be used to compute the similarity value.