Abstract: The present disclosure provides techniques for fast record matching using machine learning. One example method includes receiving a request indicating one or more attributes, identifying, from a plurality of records using a first machine learning model, a set of records, wherein each record of the set of records indicates the one or more attributes, computing, for each record of the set of records using a second machine learning model, a first relevance score for the record, computing, for each record of the set of records using a third machine learning model, a second relevance score for the record, and identifying, based on the first relevance score for each record of the set of records and the second relevance score for each record of the set of records, a given record of the set of records best matching the request.

Abstract: Mechanisms are provided for processing a sequential database natural language query. A process model is preprocessed to generate mapping data structure(s). The mapping data structure(s) map elements of the sequential process to other elements of the sequential process to thereby identify sequential and dependent characteristics of the sequential process. A sequential database natural language (SDNL) query interpretation engine is configured with the mapping data structure(s) and natural language processing is performed on a query to generate extracted features. The configured SDNL query interpretation engine operates on the extracted features and the mapping data structure(s) to generate intent information for the query. Executable database queries are generated based on the intent and executed on a database to return a response to the query.

Abstract: Techniques and devices for improving rhythmic motion of a subject are described herein. In particular, the disclosed techniques and devices utilize stimuli (acoustic, visual, tactile, and/or vibrational stimuli) delivered at beta frequencies and/or gamma frequencies to enhance neural activity and movement at delta frequencies in the subject. The disclosed techniques and devices may be used to improve motor symptoms in subjects with neurodegenerative conditions and/or to promote athletic training in healthy individuals.

Abstract: Aspects of the present disclosure provide techniques for automated health scoring through meta-learning. Embodiments include retrieving text data related to an entity that was provided by a user and providing one or more first inputs to a first machine learning model based on a subset of the text data. Embodiments include determining, based on an output from the first machine learning model, whether the text data includes an address. Embodiments include determining that the text data includes a name and determining, based on the address and the name, that one or more text results from one or more data sources relate to the entity. Embodiments include providing one or more second inputs to a second machine learning model based on the one or more text results and determining, based on an output from the second machine learning model, a health score for the entity.

Abstract: A magnet includes a magnet matrix and a bond coating arranged at a surface of the magnet matrix. The bond coating includes a thermosetting adhesive layer and a thermoplastic adhesive layer. The thermosetting adhesive layer includes a foaming agent. The thermosetting adhesive layer and the thermoplastic adhesive layer are arranged in sequence from the surface of the magnet matrix to outside.

Abstract: Aspects of the present disclosure provide techniques for efficiently utilizing physical computing resources for non-convex function approximation. Embodiments include determining a model formulation for determining a target value based on one or more constraints, wherein the model formulation comprises a non-convex function. Embodiments include converting the model formulation into a mixed integer programming (MIP) model, wherein the converting involves determining, based on the non-convex function, a first convex function and a second convex function. Embodiments include solving the MIP model, including computing a first piecewise linear approximation of the first convex function, computing a second piecewise linear approximation of the second convex function, and determining a difference between the first piecewise linear approximation and the second piecewise linear approximation to produce an approximated result of the non-convex function.

Abstract: Certain aspects of the present disclosure provide techniques for training predictive risk models based on user transaction history. An example method generally includes extracting, from a transaction history data set for a plurality of users of a software application, a plurality of features for each user of the plurality of users having records in the transaction history data set. A training data set is generated based on the extracted plurality of features for each user of the plurality of users. A plurality of predictive risk models is trained to generate a risk propensity score indicating a likelihood that a specified event will occur based on the training data set. Generally, monotonicity of one or more constraints is implemented in the model.

Abstract: An anti-corrosion treatment method for preparing sintered NdFeB magnet includes preparing a sintered NdFeB matrix, and applying a heat treatment to the sintered NdFeB matrix in an oxidizing atmosphere containing at least one of alcohol or organic acid. A ratio of oxygen partial pressure to water vapor partial pressure in the oxidizing atmosphere is in a range from 1:1 to 300:1. A temperature for the heat treatment is equal to or lower than 300° C. A time for the heat treatment is in a range from 10 minutes to 200 minutes.

Abstract: Methods, systems and computer program products for providing automated robotic process automation design generation are provided. Aspects include receiving a set of stored automated sub-processes. Aspects also include receiving a process description document that describes a desired computer automated task (CAT) process. Aspects also include identifying a plurality of candidate sub-processes based on the process description document. Aspects also include identifying at least one matching sub-process based on a comparison of each of the plurality of candidate sub-processes to the set of stored automated sub-processes. The at least one matching sub-process is a stored automated sub-process that exceeds a threshold level of similarity to a candidate sub-process. Aspects also include generating a recommendation to automatically populate a portion of a CAT design file for the desired CAT process based on the at least one matching sub-process.

Abstract: A system for automating a process using robotic process automation code includes a memory device for storing program code, and at least one processor device operatively coupled to the memory device. The at least one processor device is configured to execute program code stored on the memory device to process, based on a contextual dictionary, a process description document associated with a process to be automated by a robotic process automation system, automatically generate robotic process automation code based on the processing, and execute the robotic process automation code for automating the process.

Abstract: New question and answer (QA) pairs can be automatically discovered from a corpus of data such as online chats and conversations. Newly discovered QA pairs can augment QA database, which can be used by a computer processor or device, e.g., by a chatbot, an automated machine, and/or another. Existing QA knowledge can be used to learn the structures of QA knowledge distribution in conversations, and new QA knowledge can be automatically learned through the structure of learned QA knowledge distribution in conversations. The structure of learned QA knowledge distribution can be refined by adding more semantics based on labeled data.

Abstract: Systems and methods for segmenting a group of objects concurrently based on two or more sets of metrics are disclosed. A system is configured to obtain a set of first metrics for the group of objects, with the set of first metrics including, for each object, a first metric associated with the object. The system is also configured to obtain a set of second metrics for the group of objects, with the set of second metrics including, for each object, a second metric associated with the object. The system is also configured to segment the group of objects into one or more segments concurrently based on the set of first metrics and the set of second metrics and to generate a data set including the one or more segments. For example, entities may be segmented concurrently based on a first credit score and a second credit score of each entity.

Abstract: Systems and methods for flexible, multi-constraint risk segmentation.

Abstract: A chatbot system receives utterances of a conversation. The chatbot system constructs a conversation knowledge graph comprising one or more dialogue segments that correspond to utterances of the conversation. The chatbot system identifies a dialogue segment in the conversation knowledge graph having a contextual uncertainty that is detected based on a context model. The chatbot system generates a clarifying question for the identified dialogue segment having the contextual uncertainty. The chatbot system receives a clarifying answer from a user interface of the computing device to the clarifying question. The chatbot system updates the context model and the conversation knowledge graph based on the clarifying question and the clarifying answer to resolve the contextual uncertainty of the identified dialogue segment.

Abstract: This disclosure provides an approach to generating a label for an element of a business process model. The approach comprises obtaining at least one portion of a text segment that describes an element of a business process model. The approach further comprises applying a question-answering (QA) machine learning model to the at least one portion of the text segment to obtain a set of answers to a set of predetermined questions and generating a label for the element by combining the set of answers according to a format associated with the set of predetermined questions.

Abstract: A skilled service marketplace scheduling system and method is provided. The system can include a skilled service marketplace coordination system, one or more skilled service marketplace requester devices, and one or more skilled service marketplace provider devices. The coordination system may determine a schedule given a skilled service marketplace request and a skilled service marketplace provider schedule. The coordination system may assign a given request to a skilled service provider based on the skill level of the skilled service provider. The coordination system can account for travel time between the requester and the skilled service provider. The system may interact with third party systems, such as a parts inventory, to create the skilled service marketplace schedule. The system can confirm adequate performance of the skilled service.

Abstract: Aspects of the present invention disclose a method for consolidating of a plurality of personal bills from diverse financial sources to reflect the payments, expenses, and balances without duplication. The method includes one or more processors parsing a plurality of bills of a user, the plurality of bills including bills with varying formats. The method further includes identifying a set of bills of the plurality of bills of the user, the set of bills including related bills based at least in part on a prebuilt rule. The method further includes determining a correlation of one or more items of respective bills of the set of bills of the user based at least in part on a machine learning algorithm. The method further includes generating a consolidated bill, from the set of bills of the user, based at least in part on the determined correlation of the one or more items.

Abstract: Methods, computer program products, and systems for Robotic Process Automation (RPA) upgrade of an application are provided. A first mapping indicating relationships between UI elements in a first version of the application and UI elements in a second version of the application and a second mapping indicating relationships between one or more UI elements in a first version of an RPA code corresponding to the first version of the application and UI elements in the first version of the application are respectively obtained. A third mapping indicating relationships between the one or more UI elements in the second version of the application and one or more UI elements in a second version of the RPA code corresponding to the second version of the application is determined and based on which the second version of the RPA code corresponding to the second version of the application is generated.

Abstract: Methods, systems and computer program products for providing automated robotic process automation design generation are provided. Aspects include receiving a set of stored automated sub-processes. Aspects also include receiving a process description document that describes a desired computer automated task (CAT) process. Aspects also include identifying a plurality of candidate sub-processes based on the process description document. Aspects also include identifying at least one matching sub-process based on a comparison of each of the plurality of candidate sub-processes to the set of stored automated sub-processes. The at least one matching sub-process is a stored automated sub-process that exceeds a threshold level of similarity to a candidate sub-process. Aspects also include generating a recommendation to automatically populate a portion of a CAT design file for the desired CAT process based on the at least one matching sub-process.