Abstract: Described herein are systems, methods, and graphical user interfaces for creating conversation models that may be executed by natural language understanding systems and/or intelligent assistant systems, particularly in enterprise and corporate environments. A conversation modeling interface may allow a modeler to position a plurality of graphical conversation-element objects on a canvas region of the interface, to specify associations and relationships between the various represented conversation-elements to define a conversation flow, and to provide input data to define various parameters and characteristics of the conversation-elements of the conversation.

Abstract: Disclosed herein are embodiments of systems, methods, and products that generate semantic resolutions of wireless signals. An analytic server may train a plurality of inductive classifiers generate a respective set of deduction rules. For example, the analytic server may train a first inductive classifier to mine a first set of deduction rules matching service set identifiers (SSIDs) with business entities. As another example, the analytic server may train a second inductive classifier to mine a second set of deduction rules matching proximal groupings of wireless signals (also referred to as hyperclusters) with business entities. Upon receiving an unresolved wireless signal, the analytic server may apply at least one of the first and second set of deduction rules to assign a semantic meaning to the wireless signal.

Abstract: A system for updating application capabilities across identity and access management (IAM) platforms is provided herein. The system receives data at a central system from a plurality of data sources. The central system identifies deployed application capabilities based on data from a first data source and identifies target application capabilities from a second data source. The central system compares the one or more deployed application capabilities to the one or more target application capabilities to identify a capability gap, wherein the capability gap represents a target capability not included in the deployed application capabilities. The central system automatically selects one or more applications to update based on the identified capability gap, and the central system automatically updates the selected applications by deploying the target application capabilities not included in the deployed application capabilities to the selected applications via an IAM platform.

Abstract: Described herein is a regulatory parser that downloads and efficiently processes regulatory documents. The regulatory documents may be from different sources and may have different formats. The regulatory parser parses all of the text in the regulatory documents and converts into a predetermined, single format for downstream applications. The text is organized and stored in a structured tree, organized into one or more hierarchies with nodes storing segments of text from a regulatory document. In some embodiments, each node in the regulatory tree may represent a segment of text. Partitioning the text of a regulatory document into segments of text may make the storage and querying of the regulatory documents more manageable. The organization and structure of the structured tree may reduce the times and resources needed for accessing and searching for a regulatory citation. The structured tree may allow a user to manipulate a regulatory document or text.

Abstract: Provided herein are methods and systems for generating a chatbot. In response to a user selection of a content repository, the method can include generating a hierarchy map based on the selected content repository, translating the hierarchy map into a series of chatbot prompts, and generating a chatbot based on the series of chatbot prompts. The chatbot can be configured to guide the user to selected content within the content repository.

Abstract: Systems, methods, and graphical user interfaces (GUIs) for ingesting and enriching data regarding a plurality of entities are provided. A first data set comprising company data and a second data set comprising customer data are ingested. The first data set is processed to generate a processed data set. The first data set may be processed by applying an entity matching technique, wherein one or more data elements are generated based on whether an entity of the first data set and an entity of the second data set are commonly associated. The first data set may additionally or alternatively be processed by applying a statistical matching technique, wherein one or more predicted data elements are generated based on similarity between an entity of the first data set and one or more entities of the second data set.

Abstract: A system for generating digital flowcharts is provided. The system receives sketch image data comprising a plurality of shapes and text, and processes the sketch image data to generate flowchart data by applying a first model configured to generate shape data, applying a second model configured to generate text data, and generating linking data that associates shape data and text data. The system may generate and display a visualization of the flowchart data. The system may map the flowchart data to a region of a presentation slide and display a visualization of the flowchart data on the presentation slide.

Abstract: System and methods for generating synthetic data according to a plurality of options are provided. According to a first option, synthetic data is generated based on an indication of one or more target distributions. According to a second option, a one or more target distributions are determined based on a sample data set, and synthetic data is generated based on the determined target distribution(s). According to a third option, a temporary synthetic data set is generated based on an indication of one or more target distributions, matches between the temporary synthetic data set and a sample data set are then identified, and a synthetic data set is then generated based on the identified matches. A system may automatically determine which option to leverage based on whether a user provides a sample data set, one or more target distributions, or both.

Abstract: Systems, methods, and graphical user interfaces (GUIs) for ingesting and enriching data regarding a plurality of entities are provided. A first data set comprising company data and a second data set comprising customer data are ingested. The first data set is processed to generate a processed data set. The first data set may be processed by applying an entity matching technique, wherein one or more data elements are generated based on whether an entity of the first data set and an entity of the second data set are commonly associated. The first data set may additionally or alternatively be processed by applying a statistical matching technique, wherein one or more predicted data elements are generated based on similarity between an entity of the first data set and one or more entities of the second data set.

Abstract: Described are systems, methods, apparatuses, and computer program product embodiments for automatically processing intent-based spoken language for SLU. The disclosed solution uses a scale-free network structured conversational knowledge graph that stores nodes representative of actions, objects, and intent names and edges representative of relationships between the nodes. For all phrases (including a sentence) from the same intent, the system calculates a mean feature vector using a Universal Sentence Embedding (USE) model as a feature element. The system also employs a multi-step intent detection strategy. A graph query technique may be used to match all potential intent nodes from the trained knowledge graph. The system may compute a covariance matrix between the feature element of an input phrase and feature elements of all potential intents. The major component of the covariance matrix along with the maximum covariance may be used to determine the final intent.

Abstract: Embodiments of this disclosure relate to systems and methods for determining a set of one or more identified characteristics correlated with high performing projects. Methods include receiving communication data from a plurality of servers, the communication data associated with a plurality of conversations involving one or more users. The communication data is converted into a common format and used to generate a graph, the graph based upon characteristics identified in the communication data and users involved with the plurality of conversations. The communication data can be clustered according to the characteristics and the users, thereby generating one or more clusters around at least one of a characteristic and a user. User data and project data can be generated based on the one or more clusters and be used to determine the set of one or more identified characteristics correlated with high performing projects.

Abstract: Methods and systems for artificial intelligence (AI)-assisted document annotation and training of machine learning-based models for document data extraction are described. The methods and systems described herein take advantage of a continuous machine learning approach to create document processing pipelines that provide accurate and efficient data extraction from documents that include structured text, semi-structured text, unstructured text, or any combination thereof.

Abstract: An exemplary system and method are provided for monitoring concept drift in a trained model, such as a chatbot. The system is configured to perform a method including receiving a first dataset representing model operations executed by the trained model; applying a data processing operation to the first dataset to determine a first result data of the first dataset; determining, based on the first result data, a difference between the first result data and a second result data; determining, based on the difference, whether concept drift has occurred; and in accordance with a determination that concept drift has occurred, transmitting an instruction to update training of the trained model. The exemplary system may be implemented as a drift detection system in communication with the trained model.

Abstract: Provided are asset tracking systems for determining a location of an asset, comprising a mobile device comprising one or more detection antennas and a transmitter, and a device associated with an asset and emitting Bluetooth low energy signals, wherein the system is configured to: detect a plurality of electromagnetic signals of the environment and one or more Bluetooth low energy signals from the one or more Bluetooth low energy devices; generate a signal profile based on the plurality of electromagnetic signals; determine, based on a comparison of the signal profile to data of signal profiles at a plurality of locations in the environment, a mobile-device location in the environment; and determine, based on the mobile-device location and based on the one or more Bluetooth low energy signals, one or more asset locations in the environment.

Abstract: Systems and methods for generating and utilizing an interactive causal loop diagram using a causal loop designer are provided. In one or more examples, a computer-implemented method for creating a causal loop diagram comprising visually emphasized elements can comprise displaying a first element and a second element, wherein the first element and the second element comprise visually emphasizable elements. In response to receiving a user command to connect the first element to the second element, the method can comprise displaying a connection between the first element and the second element, wherein the connection comprises a visually emphasizable element. In one or more examples, the method comprises displaying a causal loop diagram comprising the first element, the second element, and the connection. In response to a user activating a visual emphasis tool, the method can comprise visually emphasizing one or more of the visually emphasizable elements.