International Business Machines Corporation

Scott N Gerard

Corville O Allen

Steven Lester Halter

Donna Karen Byron

Steven Jay Munroe

Alexander Pikovsky

Eric Woods

Scott Robert Carrier

Sterling Richardson Smith

David B Styles

Erik Edward Voldal

Matthew Sanchez

James E Carey

Mark Gregory Megerian

John Matthew Santosuosso

Andrew Ronald Freed

Susann Marie Keohane

Timothy P Winkler

Darryl Maurice Adderly

Aliza Rivka Heching

Robert K Tucker

Dorian B Miller

David Glenn George

Stephen Mitchell

Mohammad Arif Ul Alam

Cary Lee Bates

Nitin Gaur

Srikanth Govindaraj Tamilselvam

Samuel Scott Adams

John Kenyon Gerken, Iii

John Michael Boyer

John Arthur Medicke

Marshall Allen Lamb

Curtis Howard Brobst

Elezaveta Koumpan

Chih-Hsiang Chou

Richard Allen Saltness

Abhay Choudhary

Robert Eugene Westland

Paul Charles James Dunning

Smitashree Choudhury

Wing Yin Leung

Matthew Morehouse

Jacek Adam Piskorski

A node in a blockchain network may initiate a non-fungible token identity, establish a profile for the non-fungible token identity, receive reputation data related to the non-fungible token identity, determine, based on the reputation data, a reputation score, append the non-fungible token identity with the reputation score as a non-fungible token metadata tag, and upload the non-fungible token identity and the metadata tag to an ID repository.

Reputation profile propagation on blockchain networks

A method, computer system, and a computer program product for semantic matching is provided. The present invention may include pre-processing and normalizing a job title. The present invention may include deconstructing the job title based on at least one semantic element. The present invention may include training a machine learning model. The present invention may include creating a contextual word representation of the job title using the at least one semantic element of the job title. The present invention may include computing a similarity score for each of the at least one semantic element of the job title. The present invention may lastly include applying a weight to the computed similarity score before making a final match assessment.

Semantic matching of job titles with limited contexts

A computer-implemented method, a computer program product, and a computer system for determining skill adjacencies using a machine learning model. A computer calculates first similarity scores between first skill vectors obtained from one or more training datasets and second similarity scores between the first skill vectors and skill category vectors pre-calculated from job requisitions, using both a reference corpus word embedding model and a target corpus word embedding model. The computer generates features extracted from the first similarity scores and the second similarity scores. Based on the features, the computer trains a machine learning model for classifying combinations of skills as adjacent and non-adjacent. The machine learning model is used to determine skill adjacencies between skills extracted from the job requisitions and skills extracted from resumes.

Determining skill adjacencies using a machine learning model

A method and system to interpret sensor transmission patterns to analyze anomalies in a smart environment include obtaining a map of the smart environment, the map including an indication of obstructions and openings. The method includes determining an initial location of each sensor of a plurality of sensors in the smart environment. Each sensor emits a transmission after each detection. The method also includes identifying an initial transmission pattern associated with each sensor, and identifying a change in the initial transmission pattern of a sensor among the plurality of sensors. The change is interpreted to determine whether the change in the initial transmission pattern of the sensor among the plurality of sensors is due to movement or obstruction of the sensor. Action is taken based on a determination that the sensor among the plurality of sensors is obstructed or removed.

Interpreting sensor transmission patterns to analyze anomalies in a smart environment

Provided are embodiments for a method, system, and computer program product for operating a certified information verification service. Some embodiments include receiving an article including one or more claims, and extracting the one or more claims from the article. The one or more claims are analyzed by the one or more information verification services, and a report for the article is generated based on the analysis.

Certified information verification services

A query is for retrieving a data item of a data graph. The data graph stores representations of the data item. Each representation stores information represented by the data item in a different manner or way. Sub-queries for the query each correspond to a different representation in which the data graph stores the data item. The sub-queries are evaluated to determine an appropriate representation of the data item in satisfaction or fulfillment of the query.

Evaluation of query for data item having multiple representations in graph by evaluating sub-queries

Sub-queries for a query are determined. The query is for retrieving a data item of a data graph. The data graph stores representations of the data item. Each representation of the data item stores knowledge represented by the data item in a different way or manner. Each sub-query corresponds to a different representation by which the data graph stores the data item. The sub-queries are evaluated to determine an appropriate representation of the data item in fulfillment of the query without duplicatively traversing the data graph, such as by reusing evaluation results of the sub-queries that overlap one another.

Reusing sub-query evaluation results in evaluating query for data item having multiple representations in graph

Sub-queries for a query are ordered. The query is for retrieving a data item of a data graph. The data graph stores representations of the data item. Each representation stores information represented by the data item in a different manner or way. Each sub-query corresponds to a different representation in which the data graph stores the data item. The sub-queries are ordered in an ordered list according to likelihood that evaluation thereof will yield an appropriate or selected representation of the data item that is correct for the query and that correctly answers the query. The sub-queries within the ordered list are evaluated on a sub-query by sub-query basis, until the data item has been retrieved.

Evaluation of query for data item having multiple representations in graph on a sub-query by sub-query basis until data item has been retrieved

A method is provided for analyzing log message content. The computer-implemented method may include detecting, by at least one processor, log messages in an application code, identifying a log level assigned to each of the log messages, and performing natural language processing (NLP) analysis on each of the log messages by using at least keyword and synonym matching percentage analysis criteria. The computer-implemented method may further include determining, in response to the NLP analysis, a severity score of each of the log messages, and reclassifying, based on the severity score, the assigned log level of one or more of the log messages to a different log level.

Applying consistent log levels to application log messages

Aspects of the disclosure provide for a system. In some examples, the system comprises a first sensor associated with first and second attributes and a second sensor associated with the second attribute and a third attribute. The system further comprises a processor communicatively coupled to the first and second sensors. The processor is configured to identify a number of activations of the first sensor within a time window, identify a number of activations of the second sensor within the time window, and construct a sensor vector identifying a number of first attribute activations based on the first number of activations of the first sensor, a number of second attribute activations based on the number of activations of the first sensor and the number of activations of the second sensor, and a number of third attribute activations based on the number of activations of the second sensor.

Sensor vectors based on activations of sensors with attributes

A search engine is enhanced to employ user preferences to customize answer output by, receiving a first plurality of candidate answers and weights to a first search query for a first user from a first stage of a non-semantic search engine routing and processing path; augmenting the weights for the plurality of candidate answers according to a set of preference coefficients according to a first set of preferences for the first user; selecting one or more of the first plurality of candidate answers according to the augmented weights; and producing an output including the selected one or more candidate answers.

Enhanced answer in DeepQA system according to user preferences

Systems and methods for preventing vulnerabilities in a blockchain due to quiescence are disclosed including submitting a first crosslink transaction for addition to a first blockchain that includes cross-referencing information for a second crosslink transaction that corresponds to the first crosslink transaction and submitting the second crosslink transaction for addition to a second blockchain that includes cross-referencing information corresponding to the first crosslink transaction. The first and second crosslink transactions are configured to be usable together by a user of at least one of the first and second blockchains to validate at least a portion of one of the first and second blockchains after a period of quiescence in the one of the first and second blockchains.

Interlocked blockchains to increase blockchain security

An approach is provided to identify permanence data corresponding to terms included in a corpus of a question answering (QA) system. Based on the identified permanence, a time-based confidence of each of the terms is established. Terms are identified as a plurality of candidate answers to a question posed to the QA system. Each of the plurality of candidate answers are scored with the scoring being at least partially based on the time-based confidence established for each of the terms.

Applying level of permanence to statements to influence confidence ranking

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Research Triangle Park, NC, United States of America

Scott N Gerard