International Business Machines Corporation

Dan O'Connor

William Graham O'Keeffe

David Deidou Taieb

Ashok Kumar

Muhtar B Akbulut

Jose Barbosa

Pankaj Dhoolia

Kevin B Haverlock

Cale R Vardy

Mark Marrara

Andy James Stoneberg

Sachindra Joshi

Srikanth Govindaraj Tamilselvam

David P George

Collin James Murray

Venkat Raghavan Ganesh Sekar

A plurality of constraints associated with conversational steps implemented by a conversation model is extracted from the conversation model. Using the conversational steps and the constraints, a directed graph is constructed, each node in the directed graph representing a conversational step, each directed edge in the directed graph representing a possible execution path from a first conversational step to a second conversational step. An edge in the graph is populated with flow data denoting a probability associated with the edge. By traversing a portion of the graph, an experience preview is generated, the experience preview demonstrating a user experience of a portion of the conversation model.

Self-contained conversational experience previewing

In an approach for a cooperative build and content annotation system for conversational design of virtual assistants, a processor formulates a build context based on a build activity of a user. A processor formulates one or more content queries based on the build context. A processor builds a content index by augmenting a text-search index with a neural Information Retrieval (IR) index. A processor searches the content index using the one or more content queries to identify content relevant to the build context. A processor determines at least one recommendation for the user based on heuristic rules applied to the build context and the identified content, wherein each recommendation is a build suggestion or a content annotation suggestion.

Cooperative build and content annotation for conversational design of virtual assistants

Aspects include generation of automated response follow-up. A response to a question from a user is received at a response follow-up system. The response follow-up system analyzes the response using natural language processing to identify one or more response terms. The response follow-up system generates one or more follow-up questions based on the one or more response terms. Based on the response, one or more follow-up responses to the one or more follow-up questions are pre-fetched from one or more content provider systems including one or more content servers, where a question answering system including the response follow-up system is communicatively coupled to the one or more content provider systems through a network. The response follow-up system modifies an aspect of a user interface displayed to the user based on the one or more follow-up questions and the one or more follow-up responses.

System for generation of automated response follow-up

A mechanism is provided in a data processing system comprising at least one processor and at least one memory, the at least one memory comprising instructions which are executed by the at least one processor and configure the processor to implement a conversation scope system, comprising a conversation scope controller and a conversation scope extractor, for progressively extending conversation scope in a multi-user messaging platform. The conversation scope controller captures an utterance input by a user into a chat platform. The conversation scope extractor determines a conversation scope for the utterance based on at least one entity extracted from the entity. The conversation scope controller directs the utterance to a messaging chat room based on the determined conversation scope.

Progressively extending conversation scope in multi-user messaging platform

Aspects include engaging a user in a chat flow by a dialog system. A user sentiment associated with a system response provided by the dialog system as part of the chat flow is determined based on observation of the user. A next system response is rerouted from a planned sequence of the chat flow to a sentiment-based repair sequence to alter content delivered to the user based on a detected aspect of the user sentiment.

Conversation path rerouting in a dialog system based on user sentiment

Aspects include cross validation of user feedback in a dialog system. A repository of previous user feedback associated with a user interface is accessed. One or more identified features in the previous user feedback are classified. A sequence of cross-validation questions is generated in a dialog system to elicit further feedback from a current user of the user interface based on the one or more identified features and observed interactions of the current user with the user interface. Responses to the sequence of cross-validation questions are filtered to group the further feedback associated with the one or more identified features. One or more change suggestions to modify the user interface are stored based on the previous user feedback and the further feedback associated with the one or more identified features.

Cross validation of user feedback in a dialog system

Aspects include determination of automated response follow-up. A response to a question is received at a response follow-up system. The response follow-up system analyzes the response using natural language processing to identify one or more response terms. The response follow-up system determines one or more follow-up questions based on the one or more response terms. The response follow-up system modifies an aspect of a user interface based on the one or more follow-up questions.

System for determination of automated response follow-up

Aspects include generation of automated response follow-up. A response to a question is received at a response follow-up system. The response follow-up system analyzes the response using natural language processing to identify one or more response terms. The response follow-up system generates one or more follow-up questions based on the one or more response terms. The response follow-up system modifies an aspect of a user interface based on the one or more follow-up questions.

Context data is determined for a web page. The context data includes textual data that describes subject matter displayed on the web page. A client query is retrieved from a client-retrieved instance of the web page. An identifier associated with the web page capable of distinguishing the web page from other web pages is determined. In response to receiving the client query, a plurality of queries are retrieved from a database. Whether one or more of the retrieved queries correlate the determined web page context and the received client query is determined. A set of one or more queries from the plurality of queries is selected based on the selected set of queries each having been determined to correlate the web page context data and the client query. The selected set of the plurality of the queries is sent to the client-retrieved instance of the web page.

Growing community of inventors

Milton, MA, United States of America

Dan O'Connor