International Business Machines Corporation

Laura Irina Rusu

Gandhi Sivakumar

Amol Ashok Dhondse

Anand Pikle

Guy Sharon

John Michael Wagner

Alexe Bojovschi

Thomas Charles Conway

A cognitive proximate recommendation method, system, and non-transitory computer readable medium, include first extracting a requested feature and a requested value of the requested feature for a requested item and returning a return item from a plurality of return items stored in the database and returning a ranked list of the plurality of return items, where the ranked list further includes inter-relationships that are defined by defining a primary value of each of the requested items and the return feature corresponding to the requested feature or anchor value for each of the requested items and the return feature corresponding to the requested feature.

Cognitive proximate calculations for a return item

A corpus curation method, system, and non-transitory computer readable medium, include mapping a kinematic motion of a robot to a granular feature of an item in the corpus and answering a user question using the mapped kinematic motion embedded in an answer by the robot.

Corpus curation for action manifestation for cognitive robots

A maintenance prioritization method, system, and computer program product, include collecting information including image data and status data for a plurality of objects of interest, building a three-dimensional image for each object, and estimating a risk factor of failure for each object by analyzing the information and the three-dimensional image of the object to compare with known characteristics of the object and a reference object description.

System, method and computer program product for characterizing object status and determining a maintenance schedule

Aspects include querying, by a processing system, a workflow database for a desired target entity. The processing system traverses a dependency graph that defines one or more entity and action sequences of a workflow that result in creating the desired target entity based at least in part on failing to locate the desired target entity in the workflow database. The workflow can be a bioinformatics workflow to analyze one or more digital representations of biological data. The processing system queries the workflow database to determine an entity existence status of each entity in the one or more entity and action sequences. The processing system schedules execution of an associated action that outputs each entity identified as non-existent based at least in part on the entity existence status and the one or more entity and action sequences to create the desired target entity.

Dependency-driven workflow management

An approach for securing sensitive information in communication data is provided. In an embodiment, communication data is received from an ongoing communication (e.g., phone conversation, exchange of text messages, etc.) between a user and at least one other person. Contextual input is derived based on the content of the communication data and historical data from one or more external sources. A sensitivity index score for each element (e.g., portion) of the communication data is derived based on an assessment of the contextual input. The elements of the communication data having a sensitivity index score greater than a predefined threshold value are deemed to be security sensitive and, therefore, are encoded prior to transmission to its intended recipient.

Selective cognitive security for communication data

A method for providing bidding support to a user during an auction using cognitive modeling comprises obtaining data associated with the auction, with the obtained data comprising data associated with at least one bidder. The obtained data is analyzed, and at least one output is generated based on the analysis. The at least one output is sent to at least one device associated with the user. The at least one device is configured to generate at least one alert based on the at least one output, with the at least one alert providing decision support to the user with respect to bidding strategy.

Implementing cognitive modeling techniques to provide bidding support

A cognitive proximate recommendation method, system, and non-transitory computer readable medium, include identifying a requested item based on a user request, first extracting a requested feature and a requested value of the requested feature for the requested item, and returning a return item from a plurality of return items stored in the database by: second extracting a return feature corresponding to the requested feature for each of the plurality of return items, third extracting a return value of the return feature, and calculating a proximal distance between the return value for each of the plurality of return items and the requested value of the requested item.

System, method and recording medium for cognitive proximates

System, method, and recording medium for corpus curation for action manifestation for cognitive robots

Embodiments include method, systems and computer program products for proximity based content security. Aspects include receiving a request to access a secured data by a user device; accessing, by a processor, a security profile for the secured data; obtaining environmental data from one or more sensors related to the user device, wherein a type of the one or more sensors is determined by the security profile; and providing access to the secured data based upon a determination that the environmental data is in compliance with the security profile.

Growing community of inventors

Endeavour Hills, Australia

Laura Irina Rusu