Abstract: A method comprises receiving a request to generate a customized dataset comprising data stored onto a blockchain; retrieving user work history data associated with a user from one or more block instances of the blockchain; in response to presenting the user work history data on a display of the second computing device, receiving a selection of a subset of the user work history data from the second computing device; generating a blockchain address corresponding to one or more hash values of a subset of the one or more block instances associated with the selection of the subset of the user work history data; and transmitting the blockchain address to the second computing device.

Abstract: Provided are techniques for determining an effect of a message on a personal brand based on future goals. A message is received from an entity for a social media platform. Additional messages related to the message are identified. A reaction sentiment trend is determined for each topic of the additional messages for a period of time. An effect the message has on a personal brand of the entity in future is predicted based on future goals of the entity and based on the reaction sentiment trend for each topic. An indication of whether the message is aligned with the future goals based on the predicted effect is provided. In response to the message being aligned with the future goals, the message is posted to the social media platform. In response to the message not being aligned with the future goals, one or more suggestions to modify the message are provided.

Abstract: A management system operates in conjunction with entities to provide component recommendations for objects. The management system trains a machine learning model used to generate the component recommendations. The machine learning model is trained based on historical component entries describing components previously provided and identifiers of the components. The management system generates training data by classifying the historical component entries into predetermined component classifications. After the machine learning model is trained, the management system generates a customized recommendation of components for an object based on likelihoods of selection of the predetermined component classifications.

Abstract: A system, method and computer program product for continuous monitoring based on biometric information, includes an employee database storing employee information, including an employee name photograph; a notification server transmitting an incoming event, including an employee verification request, including a name of an employee name and a photograph of the employee to be verified; and a verification server couple to the notification server and accessing the employee database, based on the incoming event received from the notification server. The verification server determining if the name of the employee to be verified matches a name in the employee database, and if so, determining if the photograph of the employee to be verified biometrically matches a photograph corresponding to the matching name in the employee database, and if so, transmitting a positive verification result notification including multijurisdictional arrest and conviction data to a customer device via the notification server.

Abstract: A contact center service is configured, deployed, and operated for a limited term in connection with an event. Configurations to provide a contact center service for an event are defined according to a term of the event and one or more service features available for attendees of the event to use. The contact center service is deployed at or prior to the start of the term of the event according to the configurations. Responsive to deploying the contact center service, the service features are facilitated via the contact center service, such as to enable contact center engagements between agents and users as event attendees. The contact center service is eventually terminated based on an expiration of the term. Contact center as a service software used to configure, deploy, and operate the contact center service may be integrated with an event system used to implement the event.

Abstract: Among other things, embodiments of the present disclosure improve the functionality of electronic messaging and imaging software and systems by determining the current activities of users based on location sensor information from the users' computing devices and generating customized media content items based on their activities. The media content can be generated for a variety of topics and shared with other users. For example, media content (e.g., images or video) can be generated and displayed on a user's computing device, as well as transmitted to other users via electronic communications, such as short message service (SMS) or multimedia service (MMS) texts and emails.

Abstract: Among other things, embodiments of the present disclosure improve the functionality of electronic messaging and imaging software and systems by determining the current activities of users based on location sensor information from the users' computing devices and generating customized media content items based on their activities. The media content can be generated for a variety of topics and shared with other users. For example, media content (e.g., images or video) can be generated and displayed on a user's computing device, as well as transmitted to other users via electronic communications, such as short message service (SMS) or multimedia service (MMS) texts and emails.

Abstract: This disclosure describes techniques that include interpreting information about a smart contract so that the terms of the smart contract can be implemented across a diverse array of consensus networks or blockchain platforms. In one example, this disclosure describes a method that includes receiving, by a first computing device, information describing a smart contract, wherein the first computing device is included within a first plurality of computing devices, each on a first consensus network that maintains a first distributed ledger; performing, by the first computing device and in response to receiving the information describing the smart contract, operations to update the first distributed ledger; and interpreting, by at least one of the first plurality of computing devices, the information describing the smart contract to determine and perform at least one of a plurality of first smart contract operations on the first consensus network.

Abstract: A system and/or method can be provided for optimizing data-sharing in a multi-institutional application system using, where appropriate, semi-blind data-viewing in a semi-cooperative context. A method for evaluating agent quality, individual student success probability, and sharing these evaluations among a plurality of applicants to a plurality of academic programs while retaining the confidentiality of individual applicants is shown. Multiple parameters both immediate and historic are used to evaluate agent quality and individual student success probability.

Abstract: A system and/or method can be provided for improving applicant diversity by giving institutions selectable and adjustable application windows, thereby providing a number of benefits including an enriched learning environment. A similar system or method may be used to manage the availability of application windows in general to ensure that a diversity of applicant groups have an opportunity to apply.

Abstract: An apparatus comprising a communications interface configured to communicate over one or more networks, at least one processor and at least one memory including program code is provided. The at least one memory and the program code configured to, with the processor, cause the apparatus to at least receive, via the communications interface, an interparty transaction request. The interparty transaction request corresponds to an interparty transaction and identifying a first party and a second party. The apparatus generates a smart contract based on the interparty transaction request; stores a data entry indicating the generation of the smart contract to a distributed ledger; executes the smart contract to cause settlement of the interparty transaction between the first party and the second party; and stores a data entry indicating the settlement of the interparty transaction to the distributed ledger.

Abstract: The presently disclosed subject matter includes an apparatus with a processor and a memory storing code which, when executed by the processor, causes the processor to receive a data profile associated with a candidate resource, the data profile includes a set of attributes of the candidate resource which are relevant for assessing the candidate resource's suitability to satisfy a particular resource demand. The apparatus extracts an n-dimensional feature vector from the received data profile, the n-dimensional feature vector capturing aspects of the candidate resource's attributes and process said n-dimensional feature vector with a first ensemble machine learning model to generate a first suitability factor. Likewise, the apparatus process said n-dimensional feature vector with a second ensemble machine learning model to generate a second suitability factor. The apparatus determines whether to allocate the candidate resource to the particular resource demand using said first and second suitability factors.

Abstract: Aspects of the disclosure relate to enhanced chain of custody certification. A computing platform may establish, within a period of time of receiving data, a first distributed ledger that includes the data. The computing platform may receive a request to access the data. The computing platform may compute a first hash of the data indicating a state of the data prior to being accessed, and may record the first hash in a second distributed ledger. After granting data access, the computing platform may receive first information indicating actions performed on the data and second information indicating reasons for accessing the data. The computing platform may compute a second hash of the data indicating a state of the data after being accessed, and may record the second hash and the second information in the second distributed ledger. The computing platform may record, in a third distributed ledger, the first information.

Abstract: Machine learning-based approaches are used to automatically establish customer support sessions and/or assign customer support requests to customer support agents or other appropriate resources. For example, during a customer support session between a customer and a customer support agent, a trained model can process session data obtained during the session to determine prediction information (e.g., a next message prediction score, a predicted time for receiving a next message, a capacity score, etc.) The prediction information can be compared to an appropriate threshold to determine whether to establish a customer support session and/or assign a customer support request to the agent, even though the agent may otherwise be considered at capacity. In the situation it is determined to establish a session and/or assign a request to the agent, a session can be established and/or a request can be assigned to the agent based on scheduling or other information.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for generating a recommended target audience based on determining a predicted attendance utilizing a neural network approach. For example, the disclosed systems can utilize an approximate nearest neighbor algorithm to identify individuals that are within a similarity threshold of invitees for an event. In addition, the disclosed systems can implement an attendance prediction model to determine a probability of an invitee attending the event. The disclosed systems can further determine a predicted attendance for an event based on the individual probabilities. Based on identifying the similar individuals to, and the attendance probabilities for, the invitees, the disclosed systems can generate a recommended target audience to satisfy a target attendance for an event based on a predicted attendance for the event.

Abstract: A management system operates in conjunction with entities to provide component recommendations for objects. The management system trains a machine learning model used to generate the component recommendations. The machine learning model is trained based on historical component entries describing components previously provided and identifiers of the components. The management system generates training data by classifying the historical component entries into predetermined component classifications. After the machine learning model is trained, the management system generates a customized recommendation of components for an object based on likelihoods of selection of the predetermined component classifications.

Abstract: A computer-implemented method for identifying, among user electronic devices, customer electronic devices associated with genuine customers of organizations, the method being executed by a server, the method comprising: receiving, from a first user electronic device by the server, a first uniform resource locator (URL) of a first user browsing history; generating a first embedding corresponding to the first URL; comparing the first embedding with a template embedding of a plurality of template embeddings, the plurality of template embeddings having been retrieved from a genuity database; and in response to a difference between the first embedding and the template embedding being lower than an embedding difference threshold, adding the first embedding to the genuity database.

Abstract: Implementations of the present disclosure provide techniques to optimize distribution to multiple websites of online reviews associated with a merchant system. The system and method include receiving, from a merchant system associated with a merchant, assignment of a weight value corresponding to each website of a plurality of websites configured to receive a review associated with a merchant. A distribution parameter associated with the plurality of websites is received from the merchant system. A request to provide a review of the merchant is provided to a user system, the request comprising a link. Receiving from the user system, an indication associated with the link. In response to receiving the indication, identifying, by a redirection container, a first website of the plurality of websites based on the weight value corresponding to each website of the plurality of websites and the distribution parameter.

Abstract: A computing system accesses crime incident data from two or more organization systems. The crime incident data includes a first set of inputs associated with a plurality of crime incident groupings and a second set of inputs associated with incident data for incidents associated with each of the two or more organization systems. The computing system preprocesses the crime incident data to remove incidents that include suspect identifiers not present in at least two or more organization system. The computing system analyzes the preprocessed crime incident data to identify links between incidents across two or more organization systems using a trained crime linking model. The computing system generates a link between a first incident at a first organization system of the two or more organization systems and a second incident at a second organization system based on the analyzing.

Abstract: Machine learning systems for predictive targeting and optimizing engagement are described herein. In various embodiments, the system includes 1) training a first machine learning computer model to generate machine predicted outcomes; (2) determining weights based on the machine predicted outcomes; (3) generating a second machine learning computer model based on the weights; and (4) generating machine learned predictions for candidates.