Abstract: A method for updating code in a shared codebase is provided. The method includes: using artificial intelligence techniques to generate a network graph that indicates a set of dependencies between a plurality of code modules included in the shared codebase; receiving information that relates to updating a first code module from among the plurality of code modules; and determining, based on the network graph, a subset of the plurality of code modules to be impacted when the first code module is updated. The method may further include scanning release notes associated with the shared codebase, and using natural language processing techniques to determine functions that will be impacted by the update.

Abstract: A method for heuristics-based link prediction in multiplex networks may include a link prediction computer program: receiving a model for a multiplex network; defining a property matrix that specifies feature for cross-layer correlation; constructing a cross-correlation matrix from the property matrix; applying a count and weight correlation heuristic to the cross-correlation matrix, wherein the count and weight correlation heuristic counts a number of layers that contain a link between two nodes, and weights that count according to cross-layer correlations; applying a correlation weighted heuristic to the cross-correlation matrix; applying a count correlation-weighted heuristic to the cross-correlation matrix that counts the number of layers that contain a link between two nodes and weights that count according to both cross-layer correlations and values resulting from evaluating a monoplex heuristic applied to each layer in the multiplex network, resulting in output values; and identifying a missing link ba

Abstract: A method and a system for extracting and formatting financial time-series data is provided. The method includes: receiving a first set of tabular data; segmenting the first set of tabular data into a plurality of cells; determining whether each respective cell is a header cell or a content cell; for each header cell, normalizing each of a time period and a metric associated therewith; for each content cell, determining one or more column header cells and one or more row header cells associated. therewith; and generating an output table based on a result thereof.

Abstract: Systems and methods for privacy-preserving summarization of digital activity are disclosed. According to one embodiment in an information processing apparatus comprising at least one computer processor and at least one display, a privacy-preserving digital activity computer program performing the following: (1) capturing a blurred or pixelated screenshot of the at least one display; (2) identifying a plurality of computer application visible in the blurred or pixelated screenshot; (3) identifying a foreground or actively-used application out of the plurality computer applications in the blurred or pixelated screenshot; and (4) logging the visible computer applications and the foreground or actively-used application.

Abstract: A method and a system for using a graph neural network framework to implement a link prediction in a multiplex network environment is provided. The method includes: identifying a plurality of layers of a multiplex network, each respective layer including a respective plurality of nodes; for each node included in at least a first layer, providing, by a structural node label and determining a common embedding across all of the plurality of layers and an individual embedding for each individual layer; using a k-nearest approach to select a subset of the plurality of layers for performing link prediction with respect to each layer based on the determined embeddings; and performing a link prediction by determining a respective feed-forward network with respect to each layer included in the selected subset.

Abstract: Systems and methods for privacy-preserving inventory matching are disclosed. In one embodiment, in an information processing apparatus comprising at least one computer processor, a method for inventory matching may include: (1) receiving, from each of a plurality of clients, a masked submission comprising an identification of at least one security to buy or sell and a desired quantity to buy or sell; (2) aggregating the masked submissions resulting in a sum of the desired quantities to buy or sell; (3) matching at least two of the clients to conduct a transaction based on aggregation and their respective masked submissions; and (4) conducing the transaction between the matched clients.

Abstract: A method for optimizing personnel utilization is provided. The method includes: accessing first task management planning information that relates to a first project that has not been completed; using the accessed first task management planning information to identify a plurality of tasks to be performed in connection with the first project and to identify a plurality of persons to be assigned to respective tasks; retrieving historical task management information that relates to at least one project that has been completed; and adjusting at least a first portion of the first task management planning information based on the retrieved historical task management information.

Abstract: A method for providing a data-driven tool for individualized financial planning is provided. The method includes: receiving first information that relates to a user, the first information including at least one financial goal of the user; applying, to the first information, a machine learning algorithm that is uses historical data that relates to financial outcomes; calculating, based on an output of the machine learning algorithm, a probability that the at least one financial goal of the user is achievable; and determining, based on an output the machine learning algorithm, a proposed sequence of actions to be taken by the user with respect to achieving the at least one financial goal. The method may further include applying an artificial intelligence (AI) algorithm that uses a Monte Carlo tree search (MCTS) technique with respect to potential user actions.

Abstract: A method and a system for using a graph neural network framework to implement a link prediction in a multiplex network environment is provided. The method includes: identifying a plurality of layers of a multiplex network, each respective layer including a respective plurality of nodes; for each node included in at least a first layer, providing, by a structural node label and determining a common embedding across all of the plurality of layers and an individual embedding for each individual layer; using a k-nearest approach to select a subset of the plurality of layers for performing link prediction with respect to each layer based on the determined embeddings; and performing a link prediction by determining a respective feed-forward network with respect to each layer included in the selected subset.

Abstract: A method for generating schedules for a group of persons within a common workspace is provided. The method includes: receiving a first user input that relates to employee preferences; receiving a second user input that relates to at least one manager preference; receiving a third user input that relates to business constraints; generating, based on the received first, second, and third user inputs, a respective schedule for each corresponding group member; and outputting each respective schedule to a user interface for display thereon. The method may also include generating a set of metrics that corresponds to the employee preferences.

Abstract: A method for using images that represent time-series data to forecast future images depicting future values as pixelated information is provided. The method includes: receiving a first set of time-series data; converting the received first set of time-series data into a first image; and using the first image to forecast a future image depicting future values as pixelated information that corresponds to a future time interval Training sets of time-series data are used to generate historical data that provides input to a machine learning algorithm, which provides, as an output, a composite image that depicts the future values as pixelated information that reflects associated uncertainties in the value predictions.

Abstract: A method and a system for generating an interpretable embedding that corresponds to a sequence of events is provided. The method includes: receiving information that corresponds to a sequence of events that respectively correspond to interactions between a customer and an organization; determining, for each respective event, a respective product associated with the organization and a respective channel via which the event has occurred; assigning a respective sentiment to each event; computing a respective weight for each event; aggregating the computed weights with respect to the products and the channels; and using the aggregated weights to generate the interpretable embedding for the customer. The interpretable embedding is then usable for generating targeted offers to the customer, handling complaints, and preventing subsequent complaints.

Abstract: A method and a system for using a graph neural network framework to implement a link prediction in a multiplex network environment is provided. The method includes: identifying a plurality of layers of a multiplex network, each respective layer including a respective plurality of nodes; for each node included in at least a first layer, providing, by a structural node label and determining a common embedding across all of the plurality of layers and an individual embedding for each individual layer; using a k-nearest approach to select a subset of the plurality of layers for performing link prediction with respect to each layer based on the determined embeddings; and performing a link prediction by determining a respective feed-forward network with respect to each layer included in the selected subset.

Abstract: A method and a system for managing a task are provided. The method includes: receiving, from a user, a description of a first task that relates to a first project that has not been completed; generating, by using a machine learning algorithm, a plan for executing the first task based on the received description of the first task and historical task management information that relates to at least one task that has been completed; initiating an execution of the first task based on the generated plan; and tracking the execution of the first task in order to determine whether the execution is progressing in accordance with the generated plan. The historical task management information includes task-specific skill requirements and task duration.

Abstract: Systems and methods for preserving privacy in dark pool trading environments are provided. The methods include receiving buy orders that include encrypted buy order information; receiving sell orders that include encrypted sell order information; determining whether at least one received buy order matches with at least one received sell order; and when there is a match, executing a transaction based on the match. The determination is made without revealing the encrypted information to an operator of the dark pool, thereby preserving the confidentiality of the information until the transaction is executed.

Abstract: A method for optimizing personnel utilization is provided. The method includes: accessing first task management planning information that relates to a first project that has not been completed; using the accessed first task management planning information to identify a plurality of tasks to be performed in connection with the first project and to identify a plurality of persons to be assigned to respective tasks; retrieving historical task management information that relates to at least one project that has been completed; and adjusting at least a first portion of the first task management planning information based on the retrieved historical task management information.

Abstract: A method and a system for verifying that a process conforms to a standard, such as a governmental regulation or a quality standard, are provided. The method includes: obtaining first information that relates to an entity that has executed a process, the first information including an entity identification, a standard, and at least one document that relates to a result of an execution of the first process; extracting a specific type of information from the document(s); and determining, based on the extracted information, whether the execution of the process by the entity satisfies the standard. The method may also include determining a confidence level value that relates to a degree of uncertainty of the determination of whether the standard has been satisfied, and the confidence level value may be used for adjusting the standard and/or for adjusting the verification method.

Abstract: A method for updating code in a shared codebase is provided. The method includes: using artificial intelligence techniques to generate a network gaph that indicates a set of dependencies between a plurality of code modules included in the shared codebase; receiving information that relates to updating a first code module from among the plurality of code modules; and determining, based on the network graph, a subset of the plurality of code modules to be impacted when the first code module is updated. The method may further include scanning release notes associated with the shared codebase, and using natural language processing techniques to determine functions that will be impacted by the update.

Abstract: Systems and methods for multi-agent based fraud detection are disclosed. A method may include: providing a generator configuration file comprising a plurality of transaction behaviors and a number or proportion of generator agents to act in accordance with each transaction behavior; providing a detector configuration file comprising a detector parameter for a plurality of detector agents to use; generating a first set of test data using the generator agents based on the transaction behavior, wherein the first set of generated test data may include a first set of generated test transactions, and each generated test transactions may include a fraud indicator based on the transaction behavior; training a plurality of detector agents using the first set of generated test data and the detector configuration file, wherein each detector agent outputs a first trained model object; and outputting a first trained detection model based on the first trained model objects.

Abstract: Systems and methods for extracting information from a resume of an applicant and matching the applicant with a suitable position within an organization are provided. The method includes: receiving a resume that relates to an applicant; extracting, from the received resume, information that relates to applicant attributes; and generating a score that indicates a suitability level of the applicant for an available job that is associated with a team of employees within the organization. The score is generated by applying an algorithm to the applicant attributes, the job requirements, and team goals. For a set of resumes and a corresponding set of scores, an optimal assignment of resumes to jobs that maximizes the joint score is determined.