International Business Machines Corporation

General Electric Company

Ashish Rao

Mandar Mutalikdesai

Sandipto Neogi

Sheetal Srivastava

Kartikeya Vats

Sahika Genc

Yash Veer Singh

Abhijit Vishwas Patil

Gokul Swamy

Anagha M

Sudarsan Lakshminarayanan

Simardeep Singh Arneja

Pranjal Srivastava

Shivangi Tak

Yash Vardhan Singh

Arnika Kumar

Ojasvi Bhalerao

Amod Jai Ganesh Anandkumar

Rahul Reddy Nimmakayala

Shivam Ratnakar

A method and related system determine a localness measure that represents accessibility of a node connectiveness within a signed network. The method comprises, with a computer processor, receiving focus node (FN) information related to an FN of a graph representing the signed network, receiving neighbor node (NN) information related to a plurality of NNs in the signed network, and determining the localness measure based on the NN information and the FN information. The method and system also determine a harmony measure that represents importance of a node connectiveness within a signed network. The method comprises, with a computer processor, receiving source node (SN) information related to an SN of a graph representing the signed network, receiving destination node (DN) information related to a DN in the signed network, and determining the harmony measure based on the SN information and the DN information.

Global and local measures of centrality for signed and unsigned networks

An approach is provided in which the approach applies, by a first node, a first axiom to a set of data points to generate a set of first outputs. The approach applies, by a second node, a second axiom to the set of data points to generate a set of second outputs. The first node and the second node are part of a computer network that includes multiple nodes. The approach computes a first nuance based on a set of disagreements between the set of first outputs and the set of second outputs, and adjusts a reliability of the first node in the computer network based on the first nuance.

Preserving data integrity in cognitive multi-agent systems

Systems and methods are described for generating learning roadmaps from unstructured information. The systems and methods may provide for extracting a plurality of named entities from one or more corpora of information, constructing a graph based on the named entities, inducing a subgraph from the graph based on a target named entity, wherein the subgraph includes a subset of the named entities, ordering the subset of the named entities based on the subgraph, and generating a learning roadmap for the target named entity based on the ordering.

Learning roadmaps from unstructured text

An approach for enhancing user communication with a chatbot is provided. In an embodiment, a communication from a user using a chatbot application is received. One or more intents related to the user communication are identified, with each intent having a respective confidence score. Further, any number of attributes related to the user communication are extracted. If multiple viable intents are found (e.g., intents having a confidence score exceeding a predefined threshold), then relationships between the extracted attributes are derived to establish a context. Based on the context, a disambiguation question is generated to clarify an actual intent of the user.

Enhanced conversational bots processing

A method for determining a respiration rate of a subject, includes receiving a first signal and a second signal, each signal being representative of a physiological parameter of the subject. The method includes removing a cardiac artifact signal from the first signal and the second signal to generate a first processed signal and a second processed signal respectively. The method includes removing a motion artifact signal from the first processed signal and the second processed signal to generate a first periodic signal and the second processed signal respectively. The method further includes removing a residual noise signal from the first periodic signal and the second periodic signal to generate a first noise free signal and the second noise free signal respectively. The method includes generating a combined value from a first value and a second value based on the first noise free signal and the second noise free signal respectively.

Method and system for determining respiration rate

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Bengaluru, India

Ashish Rao