Abstract: Systems and methods for implementing an automation platform that is configured to analyze computing activities from a plurality of users so as to identify potential automation processes is provided. In one or more examples, a plurality of data collection agents are deployed across a plurality of computing devices and can be configured to collect and record activities performed on the computing device by one or more users of the computing devices. In one or more examples, each agent deployed on a computing device can be configured to transmit the collected data to a central server that can store the collected data in memory. The central server can be configured to collect the data from each agent and can be configured to apply one or more data science algorithms that can be configured to cluster various activities collected by the agents into groups for potential automation.

Abstract: Techniques for determining levels of interactions amongst entities in a group are provided. A plurality of mobile electronic devices detect signal data indicating when pairs of devices are proximate to one another. A receiver receives the detected signal data, and a data structure representing a contact network is generated based on the received detected signal data. Based on the contact network, a first metric is generated comprising a quantification of an average number of other entities in the contact network with which an entity in the contact network will have interactions in a predetermined amount of time. Based on the contact network, a second metric is generated comprising a quotient comprising of a size of a component of the contact network divided by an overall network size of the contact network. Based on the first and second metric, a level of interaction amongst entities in the group is determined.

Abstract: A system for automatically generating responses to user queries includes one or more processors, operable when executing instructions to: receive a query from a user, determine a first set of similarity scores between the query and a plurality of stored queries stored in a data store, and determine whether a first similarity score of the first set of similarity scores meets a first threshold. In accordance with a determination that the first similarity score meets the first threshold, the processors are further operable to obtain a set of case information for the current case; retrieve case information for at least one precedent case; determine a second set of similarity scores between the current case and the at least one precedent case; determine whether a second similarity score of the second set of similarity scores meets a second threshold; and generate a response to the query.

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: Provided is a method for generating a personalized content suggestion in response to a query from a user. The method may be performed by a system comprising one or more processors. The method may include receiving the query from the user, generating one or more user parameters associated with the user, determining a predicted content topic of the query, and generating the content suggestion based on the predicted content topic and the one or more user parameters.

Abstract: Systems and methods for generating secure ephemeral cloud-based computing resources for data operations is provided. In one or more examples, a computing hub can receive a data set as well as one or more business process instructions from an external entity. In response to receiving the data set and business process instructions, the computing hub can create one or more containers within a persistent data storage computing resource and store the data set in the one or more containers. The computing hub can generate one or more cloud-based computing resources on one or more cloud-based computing resource platforms based on the received business processes. The computing hub can be configured to arbitrate access to the stored data set from the generated cloud-based computing resources and can be also configured to track lineage information of the data set as it is process by the one or more cloud-based computing resources.

Abstract: A system for parsing journal entries is configured to receive input data comprising a plurality of journal entries from one or more data sources and consecutively parse each respective journal entry. The journal entries can be parsed according to an algorithm that selects subsets of either credit or debit records from the journal entry, identifies matching subsets of records that foot to zero when combined with the selected records, and removes subsets containing records in the matching subsets from respective credit and debit data structures.

Abstract: Hardware and/or software systems, devices, networks, and methods for managing for access authentication, and verification to devices, networks, and systems based on a wireless signal identity developed for wireless-enabled devices based on wireless signal information associated with wireless signals previously detected by the wireless-enabled devices. The system may be used to authenticate access requests, transactions, etc. based on comparison between wireless signal information associated with wireless signals presently detected by the WED and its wireless signal identity via a management platform and/or the WED itself.

Abstract: An entity trust index relating to an entity may indicate a trustworthiness level of the entity. To generate an entity trust index, entity information may be received from one or more information sources. Using the entity information and one or more machine learning models, a performance index, an innovation index, and a sustainability index for the entity may be generated. The entity trust index may be generated based on the performance index, the innovation index, and the sustainability index. One or more actions for the entity that will modify the entity trust index may then be determined.

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.