International Business Machines Corporation

Nathaniel Mills

Luis Alfonso Lastras-Montano

Sachindra Joshi

Jatin Ganhotra

David Nahamoo

Steven I Ross

Danish Contractor

Bonnie Kathryn Ray

Lazaros Polymenakos

Chulaka Gunasekara

Kshitij P Fadnis

Li Zhu

Ross Warren Judd

Jesus M Rios Aliaga

Gaurav Pandey

David H Byman

A method, computer system, and a computer program for conducting a conversational search. In one embodiment, the method includes monitoring a dialogue involving at least one user and capturing user utterances provided during the dialogue. These user utterances are then analyzed and classified according to the context of the dialogue. The dialogue is intervened upon the determination that a user needs additional information and/or upon execution of an action on behalf of the user and based on the plurality of user utterances and context. The Required information may be provided back to the user using Documentation Recommendation Module. The Documentation Recommendation Module determines a valid resource recommendation as determined by a combination of the context and a resource that includes additional information.

Techniques for predicting a personalized URL document to assist a conversation

Methods, systems, and computer program products for context-based response generation are provided herein. A method includes: obtaining conversation logs comprising agent responses matched to contexts and a set of designated responses that are not matched to the contexts; replacing at least a portion of the agent responses with the designated responses to form modified conversation logs; training a first model, using the modified conversation logs, to output a designated response in the set for a given context and a second model, using the historical conversation logs, to output one of the agent responses for a given context; identifying one or more new responses based at least in part on the output of the second machine learning model for a particular one of the contexts; and retraining the first machine learning model based at least in part on the one or more new responses.

Context-based response generation

Embodiments herein describe an automated process for identifying tasks that can be converted from primarily being driven by a human agent into bot-driven RPAs. This disclosure describes techniques for automatically generating RPAs by monitoring the actions of the agent and identifying corresponding events. These events can be performed on unstructured data sources and structured data sources. The events are clustered into different tasks where pattern detection techniques are used to identify common (or overlapping) events and causal relationships between the events. Using these causal relationships, the system can map events performed on unstructured data sources to events performed on structured data source. The system can then generate respective bot-RPAs for the tasks. The system can monitor, in real-time, data received from unstructured and/or structured data sources and when it identifies data for one of the bot-RPAs, automatically execute the RPA to perform the task.

Unstructured extensions to rpa

A computer-implemented conversational system framework to perform tasks associated with a client request. A conversation application executing on a hardware processor provides application workflow orchestration, the conversation application receiving a client request and sending one or more application requests based on the application workflow orchestration. A conversation system executing on a hardware processor provides conversation workflow orchestration, the conversation system receiving the one or more application requests. The conversation application and the conversation system develop dialog context and store the dialog context in a memory device. The conversation application and the conversation system develop the dialog context by invoking at least one micro-service to perform tasks associated with the one or more application requests. The conversation application generates a response to the client request based on the developed dialog context.

Conversational framework

Various embodiments provide a multi-channel collaborative visual analytics (CVA) system, method and computer program product for coordinating collaborative data exploration. The system comprises a central CVA server and a plurality of client devices. The CVA server has a plurality of local channels and a global channel. Each client device is coupled to one or more local channels of the central CVA server by one or more WebSockets and communicates state change event data of a distributed-web-connected application to the central CVA server. The central CVA server manages both real-time delivery and recorded playback of the state change events for the plurality of client devices. The CVA system further comprises a persistent store that stores the state change events from the plurality of client devices for deferred playback.

Collaborative multi-media, multi-channel cognitive visual analytics rationale authoring and playback

A system, method and computer program product for facilitating collaborative decision making may be provided. The system receives data representing individual postings of users associated with a deliberation to make a decision. The system further receives ratings associated with the individual postings in order to make the decision. The system represents the received data in a hierarchical data structure. The system aggregates, through the hierarchical data structure, the ratings associated with the individual postings to obtain strength values. The system facilitates the making of the decision based on the aggregated strength values.

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Coventry, CT, United States of America

Nathaniel Mills