International Business Machines Corporation

Nec Corporation

Pawan Raghunath Chowdhary

Robert John Moore

Sunhwan Lee

Hovey R Strong, Jr

Anca Andreea Chandra

Eric Kevin Butler

Divyesh Jadav

Thomas D Griffin

Jeanette L Blomberg

Shun Jiang

Markus Ettl

Heiko Hary Ludwig

Nathalie Baracaldo Angel

Chung-hao Tan

Guangjie Ren

Susanne M Glissmann-Hochstein

Zhengliang Xue

George Andrei Mihaila

Raphael I Arar

Taiga Nakamura

Hui Lei

Hung-Yang Chang

Shyh-Kwei Chen

Lei Huang

Thomas Robert Ervolina

Karthik Sourirajan

Roger Douglas Lederman

Themis Palpanas

Dinesh C Verma

Young Min Lee

Liangzhao Zeng

Hovey Raymond Strong

Margaret Helen Szymanski

Anshul Sheopuri

Jun-Jang Jeng

Shubhi Asthana

Daniel John Peters

Tim Nonner

Se Chan Oh

Ulrich B Schimpel

Hongxia Yang

Suppawong Tuarob

Donald Keefer

Amir J Safavi

Gabriel Toma

Florian Pinel

Dulce Beatriz Ponceleon

Mathews Thomas

Eric Hc Liu

Sandeep Gopisetty

Yu Tang

Charles Thomas Rettner

David James Beymer

Aly Megahed

Soumyadip Ghosh

Amit Dhurandhar

Dharmashankar Subramanian

Luisa Dominica Bozano

Luis Angel D Bathen

Andres Garagiola

Shubir Kapoor

Diego A Masini

Kumar R Virwani

Utpal Mangla

Andrea Fasoli

Eric Young Liu

Cheryl Ann Kieliszewski

Ronald Robert Labby

Bulent Nihat Kurdi

Ching-Hua Chen-Ritzo

Satishkumar Sadagopan

David Wayne Harrison

Haifeng Xi

Aminat Adebiyi

Mohammed Abdi

Alberto Mannari

Kevin P Roche

Bing Zhang

Saurabh Mishra

Gerald Coon

Themistoklis Palpanas

William Stephen Schaefer

Swanand Ravindra Kadhe

Bruce C Graves

Abubeker Abdullahi

Rohit Avinash Mujumdar

Somnath Mukherjee

Manuel Hernandez

Zhenyu Hu

Systems, methods, and computer program products for obfuscating search queries are described herein. A method comprises reading an input query; reading a set of known terms organized into hierarchical classes; determining whether the input query is included in the set of known terms; determining one or more classifications for the input query in accordance with its inclusion in the set of known terms; generating a prompt in accordance with the one or more classifications and the input query; providing the prompt to a generative language model as input; receiving, from the generative language model, a plurality of candidate queries in accordance with the prompt; determining a score for the plurality of candidate queries; and generating a plurality of decoy queries based on the plurality of candidate queries and the score.

Obfuscating search queries

A computer-implemented method, according to one approach, includes: receiving, from a remote location, a request to generate a unique equipment code identifying a device. Identifying characteristics of the device are determined, and a unique equipment code is generated. The unique equipment code is generated by applying policy based rules summarized in one or more predetermined information dependency graphs while combining at least some of the determined identifying characteristics in a specific order. Moreover, the combined identifying characteristics are converted into a corresponding alphanumeric string. The unique equipment code is assigned to the device and the unique equipment code is also transmitted to the remote location.

Managing distributed devices using unique codes

Embodiments are provided for ticket-agent matching and agent skillset development. In some embodiments, a system includes a processor that executes computer-executable components stored in memory. The computer-executable components can include a matching component that determines, using a ticket profile and a space of agent profiles, a ticket-agent pair including a ticket identifier of a service request and an agent identifier of a particular agent within a pool of agents. The computer-executable components also can include a rematching component that assigns a second agent identifier to the service request to develop a skillset of a second particular agent within the pool of agents, the second agent identifier being associated with an unsatisfactory skill score for a defined skill to resolve the service request.

Ticket-agent matching and agent skillset development

Provided is a system and method for tuning an array of sensors to enable selection of the most suitable sensors for a target application. After extracting features from sensor raw data, the extracted features are ranked with gradient boosting decision trees to assign an importance value to each extracted feature. A threshold value for the entire set of extracted features is calculated and an importance score is calculated for the individual sensors of the array. Individual sensors with an importance score on or above the threshold value are selected for the target application.

Sensor tuning&#x2014;sensor specific selection for IoT&#x2014;electronic nose application using gradient boosting decision trees

Systems, methods, and computer-readable media are disclosed for identifying customers having associated opportunities for improved growth and/or profitability with respect to product or service offerings and determining investment solutions that enhance the probability that the customers transition to the higher growth/profitability opportunities. Prior customer transactions are segmented based on segmentation criteria and used to generate a transaction graph. The nodes of the transaction graph represent the segmented transactions and client transaction paths between the nodes represent potential customer life-cycle trajectories. The transaction graph can be used to identify high-value penetration opportunities.

Dynamic management of a customer life-cycle value

Embodiments relate to an intelligent computer platform to utilize machine learning techniques to minimize compliance risk. Features are extracted from one or more data sources across two or more domains and activity data is identified. Features are identified within the activity data which are used to create one or more models. Domain activity impact is measured and a risk probability is calculated. A policy is generated based on the calculated risk probability and one or more compliance activities are orchestrated. One or more encoded actions are executed in compliance with the orchestration.

Minimizing risk using machine learning techniques

One embodiment provides a method comprising receiving a first set of information corresponding to a first entity and receiving a second set of information corresponding to a second entity. Each set of information received corresponding to each entity comprises visual information relating to the entity. The method further comprises encoding each set of information, and classifying the first entity and the second entity as either matching entities or non-matching entities based on the encoding.

Entity matching using visual information

Embodiments relate to a system, program product, and method for use and an artificial intelligence (AI) platform to identify and analyze physical forces related to sensory input. A sensor operatively coupled to an inertial measurement unit (IMU) is activated. An initial position of the IMU responsive to the sensor activation is captured and movement of the IMU from the initial position is recognized. A comparison is preformed, where the captured initial position is compared to a second position which is correlated with the recognized movement. A score based on the performed comparison is determined and a diagnostic assessment based on the performed comparison and determined score is created. The diagnostic assessment is converted to feedback, where the conversion utilizes real-time communication of an instruction of a second movement position of the IMU. Receipt of the feedback physically conveys a manifestation of the feedback to the apparatus.

Interactive exercise experience

One embodiment provides a method comprising receiving a flight plan request for a drone. The flight plan request comprises a drone identity, departure information, and arrival information. The method further comprises constructing a modified flight plan for the drone based on the flight plan request, wherein the modified flight plan represents an approved, congestion reducing, and executable flight plan for the drone, and the modified flight plan comprises a sequence of four-dimensional (4D) cells representing a planned flight path for the drone. For each 4D cell of the modified flight plan, the method further comprises attempting to place an exclusive lock on behalf of the drone on the 4D cell, and in response to a failure to place the exclusive lock on behalf of the drone on the 4D cell, rerouting the modified flight plan around the 4D cell to a random neighboring 4D cell.

Drone air traffic control and flight plan management

One embodiment provides a method including receiving authoring conversational training data. A machine learning based conversational agent is trained with the conversational training data. The training includes: creating and storing example transcripts of user utterances, creating and storing example transcripts of agent utterances, sequencing utterance transcripts using the example transcripts of user utterances and the example transcripts of agent utterances, forming a corpus from the sequenced utterance transcripts, marking speech patterns that represent social actions from tagging the sequenced utterance transcripts, and forming a patterned corpus from the marked speech patterns.

Program dialog by example

Systems, computer-implemented methods, and computer program products that can facilitate word entity disambiguation are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a language model component that employs an artificial intelligence model to generate a profile vector of an entity based on one or more binary values representing profile data of the entity and a word vector of a word entity in a dialogue based on one or more second word entities adjacent to the word entity in the dialogue. The computer executable components can further comprise a dialogue management component that disambiguates the word entity based on the profile vector and the word vector.

Contextual disambiguation of an entity in a conversation management system

One embodiment provides a method that includes generating, by a processor, a topic graph by converting information to topic nodes and edges in the topic graph. Bridges from a given topic node are provided to a neighbor node based on a weight assignment. The bridges are converted to an electronic form of communication. The processor orders suggested paths based on a determined distance from at least one other topic node to a topic goal node via an earliest topic node on each suggested path. The determined distance is found by a first search of the topic graph.

Topic bridging determination using topical graphs

Embodiments of the present invention provide a method comprising maintaining historical meeting information, receiving an event data stream corresponding to a meeting, and delaying confirmation of an assignment of a meeting room for the meeting for a period of delay defined by a confirmation condition to predict a number of in-person attendees at the meeting based on the event data stream and the historical meeting information. The meeting room is tentatively assigned to the meeting based on the predicted number of in-person attendees. The method further comprises sending confirmation of the assignment of the meeting room for the meeting to at least one invitee only after the period of delay has elapsed.

Meeting room reservation system

Embodiments of the present invention provide a method comprising receiving a task set comprising multiple tasks, receiving operational information identifying one or more operating characteristics of multiple drones, and obtaining an initial heuristic ordering of the multiple tasks based on the operational information and the climate information. Each task has a corresponding task location. The method further comprises scheduling the multiple tasks to obtain a final ordering of the multiple tasks. The final ordering represents an order in which the multiple tasks are scheduled, and the final ordering may be different from the initial heuristic ordering.

Drone carrier

Growing community of inventors

Montrose, NY, United States of America

Pawan Raghunath Chowdhary