Abstract: The Social Data Tracking Datastructures, Apparatuses, Methods and Systems (“SDTD”) transforms brokerage order request, blockchain transaction request, agency action request inputs via SDTD components into brokerage order confirmation, transaction confirmation, agency action notification outputs. An agency action request is obtained from a user of an agency oversight configured blockchain. A transaction identifier of an unwind transaction associated with the agency action request is determined. An unwind address associated with the agency action request is determined. The agency oversight configured blockchain is analyzed to determine an affected transaction for the unwind transaction, wherein the affected transaction involves unspent crypto tokens that originated from the unwind transaction. An agency blockchain transaction request that facilitates transferring crypto tokens from an address associated with the affected transaction to the unwind address is generated.

Abstract: Systems and methods for extracting data from electronic documents based on data patterns. The method includes receiving electronic template documents. Each template document corresponds to a type of electronic document. The method further includes, for each template document, processing the template document using a text extraction and data processing application. The method also includes, for each template document, determining a data extraction formula corresponding to the type of electronic document. The method further includes, storing the data extraction formula in a first database. The method also includes, receiving an electronic document including user data and a Unicode corresponding to the type of document. The method also includes, processing and classifying the electronic document into the type of document corresponding to the Unicode.

Abstract: Methods and apparatuses are described for automated predictive virtual assistant intervention. A server computing device captures clickstream data corresponding to web browsing sessions of a user at a client computing device, and generates predicted needs of the user based upon the clickstream data. The server computing device identifies virtual assistant messages for the user based upon the predicted needs of the user, and displays the identified virtual assistant messages in a virtual assistant application on the client computing device.

Abstract: Methods and apparatuses are described for normalizing digital content across databases and generating personalized content recommendations. A server normalizes structured text for each content item to generate unstructured text. The server converts the unstructured text into a multidimensional content item feature set. The server trains a model based upon user profile information, historical content consumption information, historical content recommendation information, and the feature sets. The server receives a request including a vector associated with a user of a client device. The server executes the model using the vector as input to generate interaction prediction scores. The server selects scores above a threshold and identifies content items associated with each score.

Abstract: The Tactic Tracking, Evaluation and Identification Engine Apparatuses, Methods and Systems (“TTEIE”) transforms subscription request, tick notification request inputs via TTEIE components into subscription response, identified tactic store request, user interface update notification outputs. A subscription request datastructure from a client is obtained. A set of tactic definition datastructures is retrieved. A tick notification comprising tick data for a tick associated with a target is obtained. A contact datastructure corresponding to each retrieved tactic definition datastructure is added to a tracking list of contact datastructures for the target. The tick data for the tick is appended for each contact datastructure in the tracking list. A contact datastructure's time series of ticks is evaluated with regard to the respective contact datastructure's corresponding time series of rules to classify the respective contact datastructure, for each contact datastructure in the tracking list.

Abstract: Systems and methods for authenticating a user using a voice activated device. The method includes receiving first data representing a user identifier corresponding to a user and second data representing a device identifier corresponding to the voice activated device. The method further includes determining user metadata corresponding to the user identifier and a device audio type corresponding to the device identifier. The method also includes calculating a risk score based on the user metadata. The method further includes calculating a length of spoken voice utterance based on the calculated risk score. The method also includes receiving and processing third data representing a spoken voice utterance having the calculated length corresponding to the user using the voice activated device. The method further includes validating the user in response to determining that the processed third data substantially matches the voiceprint associated with the user.

Abstract: Systems and methods for redirecting one or more printers from a virtual computing device to a physical computing device. The method includes initiating a printing application on a virtual computing device and exporting at least one printer configuration. The at least one printer configuration corresponds to one or more printers communicatively coupled to a physical computing device. The method also includes storing the at least one printer configuration to a data file on the virtual computing device and copying the data file from the virtual computing device to the physical computing device. The method further includes invoking the data file on the physical computing device such that the at least one printer configuration is imported on the physical computing device. The method also includes generating for display on the virtual computing device at least one indication of the one or more printers communicatively coupled to the physical computing device.

Abstract: Methods and apparatuses are described for enterprise access control governance in a computerized information technology (IT) architecture. A server determines access control entitlements for each of a plurality of users of the IT architecture, and converts the access control entitlements for each user into a multidimensional vector. The server generates a vector space comprising a plurality of nodes, each node in the vector space corresponding to a multidimensional vector associated with the access control entitlements. The server determines clusters of nodes in the vector space by using a similarity measure based upon dimensions of the vector. The server identifies a job role associated with each of the clusters of nodes in the vector space based upon access control entitlements that are common to the nodes. The server locates outlier nodes in the vector space positioned at least a predetermined distance away from at least one of the clusters.

Abstract: A computer-implemented method is provided for visualizing multiple objects in a computerized visual environment. The method includes displaying to a user a virtual three-dimensional space via a viewing device worn by the user, and determining a data limit of the viewing device for object rendering. The method includes presenting an initial rendering of the objects within the virtual space, where the visualization data used for the initial rendering does not exceed the data limit of the viewing device. The method also includes tracking user attention relative to the objects as the user navigates through the virtual space and determining, based on the tracking of user attention, one or more select objects from the multiple objects to which the user is paying attention. The one or more select objects are located within a viewing range of the user.

Abstract: Systems and methods for implementing historical data correction on a blockchain network. The method includes receiving historical data corresponding to a timestamp. The method also includes determining a first data block at a first address in a blockchain associated with the timestamp. The method further includes identifying a second address stored in the first data block corresponding to a second data block at the second address in the blockchain. The method also includes storing the historical data and the second address corresponding to the second data block in a third block at a third address in the blockchain. The method further includes calculating corrected metrics based on at least the historical data stored in the third data block. The method also includes generating a notification including an indication associated with the calculated corrected metrics.

Abstract: Systems and methods for implementing an end-to-end automation framework. The method includes receiving a testing data file associated with applications. The method also includes initiating a first automation framework corresponding to a first application. The method further includes storing first data generated from the first automation framework in a data file. The method also includes initiating a second automation framework corresponding to a second application. The method further includes storing second data generated from the second automation framework based on at least the first data in the data file. The method also includes generating a data log based on the data file. The method further includes generating for display the data log on a user device.

Abstract: The AI-Based Real-Time Prediction Engine Apparatuses, Methods and Systems (“AIRTPE”) transforms machine learning training input, order placement input inputs via AIRTPE components into machine learning training output, order placement output, information leakage alert outputs. An order placement datastructure associated with a security identifier is obtained. An order placement allocation for the security identifier is determined. An order placement request datastructure for a first order is sent to a server associated with a first venue. A set of trade tick data messages associated with the first venue is obtained. A set of inferred labels is determined for each obtained trade tick data message using a real-time prediction logic generated using a machine learning technique. The inferred labels of a selected inferred label type are grouped into buckets. When it is determined that the grouped inferred labels correspond to execution data generated by the first order, an information leakage alert is generated.

Abstract: Methods and apparatuses are described for user authentication in a three-dimensional (3D) alternative reality software application. A computing device coupled to an alternative reality viewing device generates a 3D virtual environment for display in the alternative reality viewing device, the 3D virtual environment comprising a plurality of 3D objects. The computing device identifies a subset of the plurality of 3D objects selected by the user of the alternative reality viewing device. The computing device captures a first set of actions of the user with respect to the subset of 3D objects, including recording a sequence of the first set of actions. The computing device generates a multidimensional authentication credential for the user based upon the first set of actions and stores the multidimensional authentication credential in a database.

Abstract: Systems and methods for extracting data from unstructured data sources based on proximity co-reference resolution model. The method includes receiving an electronic document from an unstructured data source and extracting entities from the electronic document. The method also includes receiving fields to be extracted from the electronic document and generating keywords based on the fields. Each of the entities is associated with at least one of the fields. The method further includes identifying keywords in the electronic document based on the generated keywords and calculating, for each of the fields, proximity scores based on a proximity co-reference resolution model. The method also includes, for each of the fields, identifying a field-entity pair based on the calculated proximity scores and generating for display on a user device the field-entity pair.

Abstract: The Computationally Efficient Transfer Processing, Auditing, and Search Apparatuses, Methods and Systems (“SOCOACT”) transforms smart contract request, crypto currency deposit request, crypto collateral deposit request, crypto currency transfer request, crypto collateral transfer request inputs via SOCOACT components into transaction confirmation outputs. Also, SOCOACT transforms transaction record inputs via SOCOACT components into matrix and list tuple outputs for computationally efficient auditing. A blockchain transaction data auditing apparatus comprises a blockchain recordation component, a matrix Conversion component, and a bloom filter component.

Abstract: Systems and methods for generating notifications based on extracted data from documents using a machine learning algorithm. The method includes receiving a document uploaded by a user including data corresponding to the user. The method further includes receiving an indication from the user granting permission to extract the data from the document. The method also includes extracting the data from the document using optical character recognition. The method further includes determining a document type based on the extracted data and document format data using a machine learning algorithm. The method also includes verifying the extracted data based on the determined document type and user data. The method also includes identifying a triggering event corresponding to the document based on the extracted data and the user data. The method further includes generating a notification corresponding to the triggering event.

Abstract: Methods and apparatuses are described for secure transmission and authentication of a user credential. A comprising a memory, a processor, and a laser diode identifies a first user credential comprising a sequence of alphanumeric characters, converts the first user credential into a first plurality of analog signals, activates the laser diode using the first plurality of analog signals to emit light detectable by the sensor of the second computing device. The second computing device comprising a memory, a processor, and a sensor for detecting emitted light generates a second plurality of analog signals corresponding to light emitted by the laser diode and detected by the sensor, converts the second plurality of analog signals into a second user credential, and authenticates the second user credential.

Abstract: Methods and apparatuses are described for capturing and utilizing context data in virtual assistant communication sessions. A chat-based communication session is established between a virtual assistant application and a remote device. An event manager captures a first data event of the virtual assistant application. A parent software application receives the first data event and selects one or more session context data elements using a callback function of the first data event. The event manager captures a second data event of the parent software application comprising the session context data elements. The virtual assistant receives the second data event and inserts one or more messages comprising the session context data elements from the second data event into the chat-based communication session.

Abstract: The AI-Based Neighbor Discovery Search Engine Apparatuses, Methods and Systems (“ANDSE”) transforms embedding neural network training request, object search request inputs via ANDSE components into embedding neural network response, object search response outputs. An embedding neural network training request associated with a set of context objects is obtained. Sample similarity evaluation metrics are determined. For each context object, a set of positive target samples that satisfy the sample similarity evaluation metrics for the respective context object is determined. For each context object and each positive target sample in the respective set of positive target samples, a training example comprising the respective context object and a positive target sample is added to a training set. Configuration parameters for an embedding neural network are determined. The embedding neural network is trained using training examples in the training set.

Abstract: The Dynamic Asset Sector Simulator Apparatuses, Methods and Systems (“DASS”) transforms market assumptions, constraints, portfolio construction/adjustment requests inputs via DASS components into asset allocation records, portfolio allocation and graphic presentation, seasonal portfolio investment records output. The DASS includes instructions to obtain a user indication of a portfolio simulation request including user configured market assumption parameters and retrieve a user interface template including a portfolio parameter configuration widget. The DASS's seasonal portfolio construction component may obtain economic indicator data from a data provider based on the selected collection and instantiate a regression structure employing an economic indicator. The DASS's seasonal portfolio construction component may then generate a probabilistic output indicating a probability that a current economic cycle phase belongs to the first economic cycle phase upon the instantiation of the regression structure.