International Business Machines Corporation

Raphael I Arar

Guangjie Ren

Robert John Moore

Sunhwan Lee

Shun Jiang

Pawan Raghunath Chowdhary

Hovey R Strong, Jr

Margaret Helen Szymanski

Sandeep Gopisetty

Chung-hao Tan

Chris Kau

Lei Huang

Eric Young Liu

Jonathan D Dunne

Divyesh Jadav

Eric Hc Liu

Eric Kevin Butler

Aly Megahed

Peifeng Yin

Hovey Ramond Strong, Jr

Shubhi Asthana

Cheryl Ann Kieliszewski

Kevin P Roche

Christine T Wolf

Manuel Hernandez

A computer-implemented method according to one embodiment includes determining a starting folder within a file system, computing, for each child folder of the starting folder, a similarity metric indicating a level of similarity to a file, selecting two child folders of the starting folder having greatest similarity metrics, comparing a difference between the greatest similarity metrics of the two child folders to a predetermined threshold, and conditionally selecting the starting folder as a recommended folder to which the file is saved, based on the comparing.

Suggesting a destination folder for a file to be saved

According to one embodiment, a computer-implemented method for dynamically modifying placeholder text in a conversational interface includes: processing a conversation log reflecting a conversation between a human user and an automated agent; determining, based at least in part on the processing: one or more capabilities of the automated agent; and/or a trajectory of the conversation; and dynamically modifying placeholder text in the conversational interface based at least in part on: the one or more capabilities of the automated agent; the trajectory of the conversation; or both the one or more capabilities of the automated agent and the trajectory of the conversation. Other embodiments in the form of systems and computer program products are also disclosed.

Dynamic modification of placeholder text in conversational interfaces

A computer-implemented method, system and computer program product for generating a user interface. A sketch (e.g., wireframe) of a portion of a user interface is received. The sketch is analyzed to predict a set of intended sketches using artificial intelligence based on historical data and/or the user's asset library. A set of intended final sketch renderings of the user interface is then generated and displayed using the set of predicted intended sketches based on historical data or a model trained to extract visual characteristics from existing user interface screens. If the user selects one of the intended final sketch renderings of the user interface as being directed to the intended design of the user interface and indicates that the selected intended final sketch rendering of the user interface corresponds to the final intended design, then code is generated to render the selected final sketch rendering of the user interface.

Using artificial intelligence to iteratively design a user interface through progressive feedback

One embodiment provides a method that includes obtaining a default language corpus. A second language corpus is obtained based on a second language preference. A first transcription of an utterance is received using the default language corpus and natural language processing (NLP). At least one problem word in the first transcription is determined based on an associated grammatical relevance to neighboring words in the first transcription. Upon determining that a first probability score is below a first threshold, an acoustic lookup is performed for an audible match for the problem word in the first transcription based on an associated acoustical relevance. Upon determining that a second probability score is below a second threshold, it is determined whether a match for the problem word exists in the secondary language corpus. Upon determining that the match exists in the secondary language corpus, a second transcription for the utterance is provided.

Speech-to-text transcription with multiple languages

A method, computer system, and a computer program product for matching one or more users is provided. The present invention may include collecting a user's information. The present invention may include determining that there is an overlap between the user's information and information contained within a knowledge base. The present invention may include ranking one or more matches of the user. The present invention may include displaying the ranked one or more matches to the user. The present invention may include collecting feedback from the user.

Matching users by leveraging indoor proximity and availability

One embodiment of the present invention provides a method comprising running a monitoring agent on a connected electronic device, and determining, via the monitoring agent, a level of hearing impairment of an individual user associated with the connected electronic device. The method further comprises, in response to determining the individual user has some level of hearing impairment, selecting a notification mechanism suitable for notifying the individual user based on the level of hearing impairment, and invoking the monitoring agent to notify the individual user of an event in accordance with the notification mechanism selected.

Method and system for detecting hearing impairment

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

A method, computer system, and a computer program product for feedback analysis is provided. The present invention may include, in response to identifying, using a natural language processing (NLP) component, a verb-related tag in a feedback data associated with a current version of a product or service, classifying the feedback data into a temporal class based on the identified verb-related tag. The present invention may also include, analyzing, using the NLP component, the classified feedback data within the temporal class. The present invention may further include, determining, based on the analyzed feedback data, a user perception associated with the current version of the product or service relative to the temporal class of the analyzed feedback data.

Analyzing temporal classes in user feedback

A computer-implemented method, according to one embodiment, is used to creating customized templates and template recommendations. The computer-implemented method includes: extracting text content from user information which corresponds to a user, and using the text content extracted from the user information to generate feature vectors. The feature vectors are further used to form one or more clusters of existing user editions. For each of the one or more formed clusters, a tree structure is generated for each user edition in the cluster. Moreover, the tree structures in the cluster are combined into a merged tree structure. A customized template is generated for each of the one or more formed clusters using the respective merged tree structure, and at least one of the customized templates is recommended to the user based on the user information.

Customization and recommendation of tree-structured templates

A computer-implemented method, according to one embodiment, includes: setting a target power demand corresponding to a consumer, and performing a process. The process includes: determining an actual power demand presented to a utility by the consumer, and determining a current error. The current error is the difference between the actual power demand and the target power demand. A determination is also made as to whether the actual power demand is adjustable in a direction that reduces the current error. In response to determining that the actual power demand is adjustable in the direction that reduces the current error, the current error is reduced by adjusting the actual power demand. Moreover, in response to determining that the actual power demand is not adjustable in the direction that reduces the current error, the target power demand is modified.

Computer-implemented method, system, and computer program product for setting a target power demand corresponding to a consumer

A method and system of automatically identifying topics of a conversation are provided. An electronic data package comprising a sequence of utterances between conversation entities is received by a computing device. Each utterance is classified to a corresponding social action. One or more utterances in the sequence are grouped into a segment based on a deep learning model. A similarity of topics between adjacent segments is determined. Upon determining that the similarity is above a predetermined threshold, the adjacent segments are grouped together. A transcript of the conversation including the grouping of the adjacent segments is stored in a memory.

Topic mining based on interactionally defined activity sequences

One embodiment provides a computer program product for cognitive visual and ontological mapping of tabular data. The computer program product comprises a computer readable storage medium having program instructions embodied therewith. The program instructions are executable by a processor to cause the processor to receive a data query and ontology information relating to the data query, receive context information relating to a display device, determine a measure of interest for the data query and one or more constraints for the measure of interest, determine saliency features based on the context information, and generate a user interface comprising query results corresponding to the data query arranged in a dynamic tabular format for display on the display device. The dynamic tabular format is based on the ontology information, the measure of interest, the one or more constraints for the measure of interest, and the saliency features.

Cognitive visual and ontological mapping of tabular data based on a distribution of a measure of interest

One embodiment provides a method comprising generating a conversational interface for display on an electronic device. The conversational interface facilitates a communication session between a user and an automated conversational agent. The method further comprises performing a real-time analysis of a portion of a user input in response to the user constructing the user input during the communication session, and updating the conversational interface to include real-time feedback indicative of whether the automated conversational agent understands the portion of the user input based on the analysis. The real-time feedback allows the user to adjust the user input before completing the user input.

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Santa Cruz, CA, United States of America

Raphael I Arar