International Business Machines Corporation

Robert G Farrell

Mustafa Canim

Dimitri Kanevsky

Jonathan Hudson Connell, Ii

Jonathan Lenchner

John A Gunnels

Alfio Massimiliano Gliozzo

Jason Benjamin Ellis

Tara N Sainath

Valentina Salapura

James R Kozloski

Arun Kwangil Iyengar

Brian Paul Gaucher

Mohammad Sadoghi Hamedani

Maryam Ashoori

Nicolas Rodolfo Fauceglia

Clifford A Pickover

Achille Belly Fokoue-Nkoutche

Sasha P Caskey

Thomas David Erickson

Oktie Hassanzadeh

Rachel K E Bellamy

David O S Melville

Gaetano Rossiello

Meinolf Sellmann

Sara H Basson

Sharon Mary Trewin

James Edward Christensen

Md Faisal Mahbub Chowdhury

Vijay Anand Saraswat

Ryan A Musa

Mark J Bailey

Aaron K Baughman

Peter Kenneth Malkin

Nalini Kanta Ratha

Jarir Kamel Chaar

Aditya Anand Kalyanpur

Danny Soroker

Michael Robert Glass

David W Buchanan

Sophia Krasikov

Wendy Anne Kellogg

John C Hartley

Qingzi Vera Liao

Nandana Sampath Mihindukulasooriya

Rachel Katherine Emma Bellamy

Nidhi Rajshree

Anish Mathur

Biying Kong

Nicholas Brady Garvan Monath

Frederic J Bauchot

Vittorio R Castelli

Luis Alfonso Lastras-Montano

Gerard Marmigere

John Alan Bivens

Nitendra Rajput

Akiko Suzuki

Justin David Weisz

Youngja Park

Yuan-Chi Chang

Daby Mousse Sow

John Thomas Richards

Rajarshi Das

Joel W Branch

Flemming Boegelund

Ping Zhang

Radu Florian

Avirup Sil

Jonathan H Connell

Stacy Fay Hobson

Douglas Ronald Burdick

Sarthak Dash

Sonia Mariette Embid Droz

David John Piorkowski

Frances W West

Ruben Rodriguez Torrado

Song Feng

Aaron Chavez

Bassem Makni

Tawanna R Dillahunt

Catalina M Danis

Giorgio De Paola

Douglas N Gordin

Md Arafat Sultan

Steven D Daniels

David Osmond Scott Melville

Mudita Singhal

Rajarsh Idas

Cristina Ibanez-Llano

Ana Smith

Protective barrier pole

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.

Establishing a logical connection between an indirect utterance and a transaction

A system, method, and apparatus for concealing searches for information stored on public networks, includes splitting of a search query, transforming the query into one or more related queries, and searching each of related queries separately.

Curtailing search engines from obtaining and controlling information

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.

Filtering spurious knowledge graph relationships between labeled entities

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.

Organizing fragments of meaningful text

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.

Relation extraction from text using machine learning

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.

Encoding entity representations for cross-document coreference

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.

Performing fine-grained question type classification

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&#x2014;sub-term glossary can be generated from the corpus, the preliminary super-term&#x2014;sub-term glossary containing one or more super-term&#x2014;sub-term pairs. A super-term&#x2014;sub-term pair can be filtered from the preliminary super-term&#x2014;sub-term glossary, responsive to detecting that the super-term&#x2014;sub-term pair is not a candidate for hyponym-hypernym pair, to generate a final super-term&#x2014;sub-term glossary. The preliminary candidate list of hyponym-hypernym pairs and the final super-term&#x2014;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.

Unsupervised hypernym induction machine learning

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.

System, method and computer program product for detecting policy violations

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.

Adapting dialog models by relevance value for concepts to complete a task

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.

Extracting a knowledge graph from program source code

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.

Agent to bot transfer

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.

Modulating attention of responsible parties to predicted dangers of self-driving cars

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.

Dynamic faceted search on a document corpus

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Cornwall, NY, United States of America

Robert G Farrell