International Business Machines Corporation

Vinod Muthusamy

Vatche Isahagian

Yara Rizk

Jaydeep Sen

Tarun Tater

Siyu Huo

Prabhat Maddikunta Reddy

Sampath Dechu

Rania Yousef Khalaf

Merve Unuvar

Sebastian Carbajales

Yasaman Khazaeni

Tathagata Chakraborti

Kushal Mukherjee

Prerna Agarwal

Allen Vi Cuong Chan

Dario Andres Silva Moran

Yazan Obeidi

Sarath Sreedharan

Embodiments of the invention are directed to a programmable computer system that includes a processor system operable to perform processor system operations. The processor system operations include using a workflow composer to perform an automated workflow composition process that generates a composed workflow that is operable to, when executed by a host device, satisfy a target logical goal. Performing the automated workflow composition process includes using a workflow-metric model to control the automated workflow composition process such that the composed workflow is operable to, when executed by the host device, satisfy the target logical goal in a manner that optimizes a target metric goal. The target metric goal quantifies a performance feature of the composed workflow.

Automated workflow composer using unmodeled metric-based goals

A query can be received from a user. The query can be sent to a plurality of automated agents to process the query. Results and associated confidence scores can be received from the plurality of automated agents. At least some of the results and associated confidence scores can be probed, based at least on a reason given for a result having the highest associated confidence score among the received results and associated confidence scores, to select an automated agent from the plurality of automated agents for answering the query. Information can be stored, where the information can include at least the results and associated confidence scores and a selected automated agent for answering the query, where at least one of the plurality of automated agents learns from the stored information to update its confidence score in answering the query.

Adaptive answer confidence scoring by agents in multi-agent system

A method, computer system, and a computer program product for generating a conversational bot for an application programming interface (API) is provided. The present invention may include parsing an API schema. The present invention may include generating sentences for the conversational bot from the parsed API schema. The present invention may include constructing the conversational bot by training a deep learning model. The present invention may include receiving a natural language expression from a user. The present invention may include determining whether the natural language expression is enough to activate the bot.

Generating and updating conversational artifacts from APIS

Aspects of the present disclosure relate to audio/video (A/V) stream functionality verification. A stream segment of a video feed prior to transmission over a network as captured by a transmitting device within a web-based conference can be stored. A stream segment of the video feed after transmission over the network as received by a receiving device within the web-based conference can be stored. The stream segment of the video feed prior to transmission over the network can be compared with the stream segment of the video feed after transmission over the network to determine a video feed quality.

Audio/video (A/V) functionality verification

An embodiment for identifying and processing poly-process natural language queries may include receiving a natural language query. The embodiment may also automatically identify a bridge entity in the received natural language query. The embodiment may also automatically determine whether the received natural language query is a poly-process query. The embodiment may further include, in response to identifying that the received natural language query is the poly-process query, automatically generating sub-queries for each process in the poly-process query and generate results for each sub-query. The embodiment may also automatically combining the results of each sub-query using the bridge entity to output a combined result. The embodiment may further include automatically generating a modified sub-query for post-processing of the combined result. The embodiment may also automatically process the modified sub-query to generate a final query result for the received natural language query.

Identifying and processing poly-process natural language queries

A method, computer system, and a computer program product for anomaly detection is provided. The present invention may include converting business process logs into a graphical data structure. The present invention may include generating an optimized graph encoding for anomaly detection using an unsupervised machine learning model. The present invention may include computing an anomaly score for each activity of the business process log using a process aware metric based on feature representation. The present invention may include labeling each of the one or more data points with a high anomaly score.

Graph encoders for business process anomaly detection

Growing community of inventors

Austin, TX, United States of America

Vinod Muthusamy