International Business Machines Corporation

Beat Buesser

Bei Chen

Akihiro Kishimoto

Adi Ionel Botea

Mathieu Sinn

Ngoc Minh Tran

Ambrish Rawat

Martin Wistuba

Thanh Lam Hoang

Yufang Hou

Maria-Irina Nicolae

Sean A McKenna

Seshu Tirupathi

Killian Levacher

John Savage

Radu Marinescu

Charles Arthur Jochim

Hiroshi Kajino

Michele Gazzetti

Marco Simioni

Vincent Lonij

Yiannis Gkoufas

Kostas Katrinis

Takahiko Koyama

Carlos Alzate

Ernesto Diaz-Aviles

Sharon Qian

Suwen Lin

Kelsey Dipietro

A system receives messaging, video and/or audio input streams including dialogue spoken by users at a group meeting. From these inputs, the system obtains single or multiple interaction records including natural language text memorializing content spoken by each speaker at a meeting, analyzes the content, and identifies single or multiple action item tasks in the interaction records. The system then generates summaries indicating the action item tasks for the users. From the dialogue content, the system further detects whether each action item is addressed, and whether the action item for a user has a solution, or not. The system further detects whether one action item is a precondition for resolving another action item by the user or in conjunction with another user. Using a pre-configured template, the system generates action item summaries, any associated solution, and any relationship or precondition between action items and presents the summary to a user.

Generating summary and next actions in real-time for multiple users from interaction records in natural language

One or more systems, devices, computer program products and/or computer-implemented methods of use provided herein relate to facilitating code development by predicting one or more code attributes and/or code portions for use in a project code to be written. A system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components can comprise a dialogue component that generates a query based on a natural language request comprising a code-related attribute, and a prediction component that predicts another attribute or a code portion to satisfy the request. In an embodiment, an input dataset employed to support the influence mapping can comprise time-stamped tuple data comprising a state, an action and a reward. The code-related attribute can at least partially define a project code, of code to be written.

Dialogue- and machine learning-facilitated code development

In an approach for discourse-level text optimization, a processor receives an initial text in a first language. A processor applies one or more operators to modify the initial text. A processor evaluates the modified text using a scoring function. A processor determines whether a score generated from the scoring function on the modified text is above a predefined threshold. In response to determining the score is above the predefined threshold, a processor outputs the modified text.

Discourse-level text optimization based on artificial intelligence planning

Embodiments for intelligent dynamic parking for autonomous vehicles by a processor. A dynamic parking plan may be determined for an autonomous vehicle to travel from a selected location and returning to the selected location within a selected time window according to a transportation network and one or more a variable parking functions in lieu of waiting at the selected location.

Intelligent dynamic parking for autonomous vehicles

Embodiments for intelligent discovery of preferred chemical reaction pathways to a synthesized target compound by a processor. Target compound data of a target compound a user intends to synthesize may be received. A preference score for one or more chemical reaction pathways to the target compound may be calculated based on one or more chemical reactions. One or more preferred chemical reaction pathways to the targeted compound may be determined using a modified retrosynthetic analysis according to the preference score for one or more chemical reactions.

Intelligent personalized chemical synthesis planning

Various embodiments are provided for securing machine learning models by one or more processors in a computing system. One or more hardened machine learning models that are secured against adversarial attacks are provided by applying one or more of a plurality of combinations of selected preprocessing operations from one or more machine learning models, a data set used for hardening the one or more machine learning models, a list of preprocessors, and a selected number of learners.

Learning input preprocessing to harden machine learning models

Embodiments for detection of energy consumption anomalies in one or more energy consumption systems in a cloud computing environment by a processor. Energy consumption anomalies associated with a selected facility, a selected object, or a combination thereof may be detected and diagnosed according to feedback and simulation data generated from a scenario-based simulation operation.

Operational energy consumption anomalies in intelligent energy consumption systems

Embodiments describe an approach for coordinating the travel of multiple vehicles traveling to a target destination, the embodiments describe generating a travel group, receiving travel group parameters from travel group members, synced GPS applications, and a weather application, generating a course of travel for the travel group members to reach a destination, and tracking each travel group member according to locations identified by the synced GPS applications. Additionally, embodiments describe determining that a subgroup of the travel group is no longer traveling within a pre-determined range of other travel group members; calculating an optimized course of travel for the subgroup to reunite with the other travel group members, adjusting the course of travel to include the optimized course of action for the subgroup, and causing each GPS application to direct the subgroup to travel according to the optimized course of travel.

Coordination management of multiple vehicles

Various embodiments are provided for intelligent selection of time series models by one or more processors in a computing system. Time series data may be received from a user, one or more computing devices, sensors, or a combination thereof. One or more optimal time series models may be selected upon using and/or evaluating one or more recurrent neural networks models that are trained or pre-trained using simulated time series data or historical time series data, or a combination thereof for one or more predictive analytical tasks relating to the received time series data.

Intelligent selection of time series models

Embodiments for using an intelligent transaction optimization assistant by a processor. One or more actions to enhance a transaction experience of one or more users may be provided according to one or more selected constraints learned via a machine learning operation from previous transaction experiences, user behavior relating to the one or more previous transaction experiences, transaction experiences shared amongst entities associated with a social network, or a combination thereof.

Intelligent transaction optimization assistant

Various embodiments are provided for automating decision making for a neural architecture search by one or more processors in a computing system. One or more specifications may be automatically selected for a dataset, tasks, and one or more constraints for a neural architecture search. The neural architecture search may be performed based on the one or more specifications. A deep learning model may be suggested, predicted, and/or configured for the dataset, the tasks, and the one or more constraints based on the neural architecture search.

Automated decision making for neural architecture search

Embodiments for providing data content consumption support by a processor. Data from one or more data sources may be captured and received by one or more data capturing devices while a user is consuming the data on the one or more data sources. A domain knowledge may be automatically updated with the data. A response may be provided to one or more queries based upon information accessed from the knowledge domain.

Intelligent reading support

A method, computer system, and a computer program product for text data protection is provided. The present invention may include receiving a text data. The present invention may also include identifying a portion of the received text data having a highest impact on a first confidence score associated with a target model prediction. The present invention may further include generating at least one semantically equivalent text relative to the identified portion of the received text data. The present invention may also include determining that the generated at least one semantically equivalent text produces a second confidence score associated with the target model prediction that is less than the first confidence score associated with the target model prediction. The present invention may further include generating a prompt to suggest modifying the identified portion of the received text data using the generated at least one semantically equivalent text.

Text data protection against automated analysis

Embodiments for automatic visualization and explanation of feature learning output for predictive modeling in a computing environment by a processor. A degree of importance score may be assigned to one or more features from a relational database according to the machine learning model. A visualization graph of one or more join paths and the one or more features with the degree of importance score to predict a target variable may be generated.

Automatic visualization and explanation of feature learning output from a relational database for predictive modelling

Embodiments for an intelligent directing service in an Internet of Things (IoT) computing environment by a processor. One or more objects may be identified within a defined region relative to an entity. At least a portion of an extremity of the entity may be directed to select or avoid the one or more objects according to one or more internet of things (IoT) devices.

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Beat Buesser