Abstract: A method and system for generating a unique character string based on attribute information are disclosed. The method includes receiving transaction information of a non-standard transaction, extracting various attributes from the received transaction information, and dynamically generating a character string using a combination of the various attributes. The method further includes identifying a vendor identifier that corresponds with a set of attributes stored at a vendor device that matches with the various attributes of the dynamically generated character string, and consolidating the vendor identifier with the dynamically generated unique identifier for generating a unique consolidated identifier for the non-standard transaction.

Abstract: A method for using graphical model tools to evaluate classification models that are trained by using incomplete data sets for which data is known to be missing and the missing data is known to be non-random is provided. The method includes: receiving first information that relates to first data to be used for training and evaluating a performance of a first classification model; analyzing the first information to determine second information that relates to missing data; generating a missingness graph that relates to a description of how the missing data has come to be missing; decomposing, based on the missingness graph, an expression that relates to a classification metric into recoverable terms and non-recoverable terms; training a second classification model to generate respective weights for the recoverable terms; and calculating, based on the non-recoverable terms, an upper bound and a lower bound on the classification metric.

Abstract: A method and system for performing a neural level vulnerability detection are disclosed. The method includes receiving a neural network model, performing a bit-level corruption check on the received neural network model indicating a potential presence of an embedded malware in the neural network model, and deploying the neural network model. The method further includes scheduling a periodic anomaly detection on the deployed neural network model, performing the periodic anomaly detection on the deployed neural network model for detecting an anomaly at a scheduled time, and when the anomaly is detected on the neural network model, executing an explainable artificial intelligence based embedded malware exploration to identify an alteration made by the embedded malware at a neuron level of the neural network model.

Abstract: A method for evaluating classification models that are trained by using incomplete data sets for which data is known to be missing and the missing data is known to be non-random is provided. The method includes: receiving first information that relates to data to be used for training and evaluating a performance of a classification model that is designed to make a determination with respect to a particular query; analyzing the first information to determine second information that relates to a known portion of the first information and third information that relates to missing data; estimating, based on the third information, an uncertainty that corresponds to the missing data; and calculating, based on the second information and the estimated uncertainty, a first Gaussian approximation to a performance metric that relates to the first classification model.

Abstract: A method for using an artificial intelligence (AI) technique to forecast market activities by specific parties with respect to derivatives and other specific types of financial instruments is provided. The method includes: retrieving first information that relates to at least one form that corresponds to a government filing; generating, based on the first information, a first knowledge graph that relates to an entity, such as a commercial concern; retrieving second information that relates to historical actions performed by at least one person that is associated with the entity; and forecasting, based on the first knowledge graph and the second information, at least one proposed future transaction to be executed by the person with respect to the first entity. The forecasting is based on an application of an AI algorithm to the information retrieved from the government filing(s).

Abstract: A system for expeditiously de-archiving archived objects. The system may include operations that comprise: configuring a first application programing interface (API) gateway between an auxiliary memory system and a repository of archived objects; receiving, via an application, a first user request for a first archived object that is stored within the repository of archived objects; processing the first user request to retrieve the first archived object; pushing, via the first API gateway, the first archived object into the auxiliary memory system that provides high-speed access to objects within the auxiliary memory system; and updating first metadata for the first archived object to store a first log of the retrieving and the pushing.

Abstract: A method for using an artificial intelligence (AI) technique to forecast trading behavior and thematic concepts for trade baskets with respect to derivatives and other specific types of financial instruments is provided. The method includes: retrieving, from an internet website, information that relates to at least one form that corresponds to a government filing; using the retrieved information to generate a knowledge graph that relates to a particular entity; generating at least one application programming interface (API) that is configured to analyze the retrieved information and the knowledge graph in order to provide insight into at least one financial instrument that relates to the particular entity; and forecasting, based on an output of the API(s) and by applying an AI algorithm to the knowledge graph, at least one proposed future transaction to be executed with respect to the financial instrument(s) that relate to the particular entity.

Abstract: A method for interpreting structured and unstructured content to facilitate tailored transactions is provided. The method includes acquiring, from one or more unstructured data sources, unstructured data, and acquiring, from one or more structured data sources, structured data. The method further includes performing natural language processing (NLP) on both the structured data and the unstructured data using a machine learning algorithm, and generating, via the machine learning algorithm, an NLP response based on the NLP. Based on the NLP response, the method further performs identifying at least one candidate object, and generating a list of actions corresponding to the candidate object.

Abstract: A method and a system for automatically processing financial documents to generate knowledge graphs that convey information relating to entities of interest and relationships between those entities are provided. The method includes: receiving a document; extracting raw text included in the document; identifying, based on the extracted raw text, a set of entities that are named in the document; determining respective relationship information that corresponds to respective pairs of entities; constructing a knowledge graph that illustrates respective relationships among the respective pairs of entities; and outputting the knowledge graph. The determination of the respective relationship information may be performed by applying an artificial intelligence (AI) algorithm that is trained by using historical data that relates to the set of entities.

Abstract: A method and a system for generating domain-aware captions for time-series images that are capable of adapting to new domains without retraining are provided. The method includes: receiving information that relates to a first time-series image that is associated with a target domain; generating a generic caption for the first time-series image; extracting, from a memory based on the generic caption, a plurality of image-caption pairs; generating, for each respective one of the plurality of image-caption pairs, a corresponding domain-agnostic caption that includes information that describes a shape of the respective image; and adapting the generic caption into a domain-specific caption for the first time-series image that relates to the target domain. The generating of domain-agnostic captions and domain-specific captions may be performed by using models that are respectively trained based on synthetic time series images having captions that correspond to a set of parameters.

Abstract: A method and system for accounting for missing not-at-random (MNAR) data in training dataset via Bayesian regularization are disclosed. The method includes acquiring historical data of an organization, the historical data including the MNAR data. The method further includes performing estimation for two of at least three unknown quantities based on the historical data, and injecting quantitative information for remaining one of the at least three unknown quantities based on qualitative information regarding nature of missingness. Lastly, the method reassembles the estimation for two of the at least three unknown quantities and injected quantitative information for the remaining one of the at least three unknown quantities, to provide a modified function.

Abstract: A method for providing a synthetic neural data model is disclosed. The method includes generating a model that simulates an electronic communication network; appending agents to the model, the agents relating to a software component that sends orders to the model based on a predetermined timestep; assigning a fixed grid to the model, the fixed grid including a tick size that relates to a fixed granularity; calibrating each of the agents by using a calibration data set; inputting the model and historical book data to a neural network; and training, via the neural network, a neural network extension of the model by using an optimizer.

Abstract: A method and computing apparatus for extracting information from a document are provided. The method includes receiving a document, extracting data from the document, assigning the document to a category from among a predetermined plurality of categories based on a result of the extracted data, and generating a structured output by formatting the extracted data based on the assigned category.

Abstract: Systems and methods for identifying blockchain address owners using test funds are disclosed. According to one embodiment, a method for identifying blockchain address owners using test funds may include: identifying, by an identity identification computer program executed by an electronic device, a room identifier for an application deployed to a test blockchain network for a main blockchain network; fetching, by the identity identification computer program, chat messages for the room identifier; extracting, by the identity identification computer program, identifying information from the chat messages; and outputting, by the identity identification computer program, the identifying information.

Abstract: A gateway interfacing with multiple distributed ledger networks may receive, from a buyer on a first distributed ledger network, a request to purchase an asset in exchange for a cash token, the asset being sold by a seller on a second distributed ledger network and an entry on the second distributed ledger network, and the cash token is an entry on the first distributed ledger network; communicate the request to the seller; receive acceptance of the request from the seller; transfer the asset to an electronic wallet for the buyer by updating ownership of the asset on the second distributed ledger network and on the first distributed ledger network; and transfer the cash token to an electronic wallet for the seller by updating ownership of the cash token on the second distributed ledger network and on the first distributed ledger network.

Abstract: Systems and methods are provided for integrated healthcare management. The systems and methods include establishing a medical record data, accessing information about a treatment related to the medical record data, obtaining biometric data related to the treatment, processing the biometric data, determining whether the treatment is appropriate with respect to the biometric data, in response to the treatment being appropriate with respect to the biometric data, administering medication, and in response the treatment not being appropriate with respect to the biometric data, determining a new treatment, and administering new medication based on the new treatment.

Abstract: A method and system for reducing false-positives using a neural network are disclosed. The method includes receiving a data envelope, scanning the data envelope and detecting a presence of data corresponding to a value in a list of sanctioned entities. The method further includes transforming format of the data envelope into a text format, identifying and extracting target information including the data corresponding to the value in the list of sanctioned entities and surrounding information, and reformatting the extracted target information and surrounding information into a natural language question. Once the natural language question is provided, the natural language question is processed by a neural network model for determining whether a sanctioned entity is included or not based on context provided by the natural language question.

Abstract: A method for automating a process of generating messages that are responsive to client inquiries by using an AI algorithm that implements a machine learning technique to ensure accuracy and timeliness in the responses is provided. The method includes: receiving a first message that includes an inquiry that relates to an account associated with a user; applying an AI algorithm for analyzing the first message in order to extract information that relates to the inquiry; determining, based on a result of the analysis, whether generating a response to the inquiry requires human intervention; when human intervention is not required, retrieving information that is responsive to the inquiry from a memory; generating a second message that includes the information that is responsive to the inquiry; and transmitting the second message to the user.

Abstract: A method for facilitating resource management by using predictive analytics is disclosed. The method includes aggregating, via an application programming interface, data from various sources, the data including end user data, resource data, and influential factor data; generating data products based on the aggregated data, the data products including a structured data set, an application, and a tool; training a first model by using the generated data products; determining predictive outputs by using the trained first model and the generated data products, each of the predictive outputs corresponding to a recommended action for management of resources; and publishing the predictive outputs to a downstream application.

Abstract: A system configured to: determine an optimal migration cache size; interface with a source database; index each respective entry from among the plurality of database record entries based on their respective database record entry dates; respectively prioritize each entry from among the plurality of database record entries for migration based on their plurality of respective database record entry dates and sizes; queue a queue of unmigrated database record entries for migration based on each respective prioritization; initiate a migration of each respective entry from among the queue of unmigrated database record entries; monitor a respective progress of the migration of each respective entry from among the queue; and provide a status of the respective progress of the migration of each respective entry from among the plurality of database record entries.