Abstract: A system and method for modifying a system's execution logic without changing the code. The system and method can involve receiving a request for execution, fetching an instruction set that corresponds to the request, parsing the instruction set, extracting metadata from the request, loading data for the instruction set based on the request, and executing each instruction based on the loaded data.

Abstract: Managing tasks using an application-level blue-green topology with parallel cell infrastructure rails. Each cell infrastructure rail includes a dispatcher bot and a performer bot. The dispatcher bot is configured to prepare a work task based on a received request, and the performer bot performs the work task, resulting in performed work. A discovery server includes a service registry configured to store the states of the infrastructure rails. The discovery server receives the request for the work task, and sends the request to a dispatcher bot of a specific cell infrastructure rail based on the request and the states of the cell infrastructure rails. A respective workflow cell server receives the performed work. In the case that one cell infrastructure rail experiences a problem when processing the request, the cell infrastructure rails are switched to perform the request on the other cell infrastructure rail. The method implements the system.

Abstract: Systems and methods for remote badging and/or computer access, automatic individual verification, automatic vaccine verification and/or automatically remotely determining an individual's physical presence at a site are provided. The systems and methods include automatic vaccine proof verification.

Abstract: A computerized system and method may be used for exchanging data over a communication network, for example based on network requests specifying inventory items in fractional amounts. A computerized system including one or more processors, a memory, and a communication interface to communicate via a communication network with remote computing devices, may be used for automatically organizing network requests in a queue; assigning a priority to one or more of the requests based on request types; tracking an auxiliary database, which may include comparing a request amount to a value in the auxiliary database, where the value may be reserved based on the priority of the request; and attempting the executing of requests based on the tracking of the auxiliary database and/or based on the queue. Some embodiments may be used as a standardized framework for fractional inventory management to be used, e.g., in cloud computing and/or fractional trading platforms.

Abstract: Automated systems and methods are presented herein for hybrid mobile apps to achieve parity with native mobile app user experiences and functionality. An exemplary system includes a mobile device running a hybrid mobile application, the hybrid mobile application comprising one or more native layers and one or more web layers, each made up of one or more native or web based tools or components respectively; the hybrid mobile application, when executed by the processor, comprises at least one app feature that improves app experiences via one or more APIs that communicate between a web layer and a native layer enabling a native mobile app user experience using one or more features or functions on at least one of the web layer and native mobile app layer.

Abstract: A system and method for detecting malware in portable executable (PE) files is provided. The system and method can include receiving a PE file, parsing the PE file to filter known malware, decompiling the filtered PE file into assembly code and/or p-code, extracting all API call sequences from the p-code, for all API call sequences that match a stored API call sequence, and/or identify the corresponding PE file as malware.

Abstract: At least one processor is configured for defining a plurality of mutually exclusive customer treatment groups, including in accordance with first and second algorithms, to receive content items. Content items are respectively provided to a random customer treatment group as well as first and second algorithm customer treatment groups, and metrics representing at least engagement by each of the customers are determined and analyzed. A selection of the first or the second algorithm is made. The at least one processor is configured to provide, to at least some of the plurality of customers, content items in accordance with the selected algorithm.

Abstract: A computer-implemented method for providing recommendations for matching leads to advisors using a machine learning model.

Abstract: A computer-implemented method for automatically analyzing handwritten text to determine a mismatch between a purported writer and an actual writer is disclosed. The method comprises receiving two samples of digitized handwriting each allegedly created by one individual and received and entered into a digital system by another. The method further comprises performing a series of feature extractions to convert the samples into two vectors of extracted features; automatically clustering a set of vectors such that the first vector and the second vector are assigned to the same cluster among multiple clusters, based on vector similarity; and automatically determining that a same individual being associated with both the first and second samples indicates a heightened probability that the individual fraudulently created both samples. Finally, the method comprises automatically transmitting a message to flag additional samples of digitized handwriting entered into a digital system as possibly fraudulent.

Abstract: A system and method generate recommendations with cold starts. The system comprises a hardware-based processor, a memory, and a set of modules. The memory stores item taxonomy data for at least one item, stores client descriptive data for at least one client, and stores historical response data for at least one item responded to by the at least one client. The set of modules includes a machine learning module and a recommendation module. The machine learning module generates a response probability matrix using the historical response data, the item taxonomy data, and the client descriptive data. The recommendation module generates and outputs a recommendation corresponding to input data using the information deduced in the response probability matrix. The method implements the system.

Abstract: Computer-implemented methods and systems are disclosed for receiving and indexing a plurality of files for later querying, for dynamically generating scripts to be executed during a query of a data store, and for horizontally distributing a query and aggregating results of the distributed query.

Abstract: Computer-implemented methods and systems are disclosed for receiving and indexing a plurality of files for later querying, for dynamically generating scripts to be executed during a query of a data store, and for horizontally distributing a query and aggregating results of the distributed query.

Abstract: Computer-implemented systems and methods update rules engines in a distributed computer system with new rules in a lightweight, non-intrusive, real-time manner. Rules engines are subscribed to a pub/sub service for new rules pertaining to a topic. A rules manager publishes a new rule to the pub/sub service with an associated topic. The rules engines download the new rule and store the new rule in-memory for execution without downtime.

Abstract: Computer systems and methods for a research organization compute interests of clients in research work product, and, using deep learning and embedding techniques, digitalize client interest profiles and research content entities. A first machine learning model is trained to compute client-interest scores from, at least in part, client engagement data. The computer system is also configured to compute embeddings for each of the clients and embeddings for each of certain research topics. The embeddings are computed using a second machine learning model, such as deep artificial neural network, such that embeddings for clients with similar interests are close, distance-wise, in a client embedding space, and such that embeddings for certain research topics with similar client engagements are close, distance-wise, in a research topic embedding space. The second machine learning model can be trained with both positive and negative training samples generated from the client-interest scores.

Abstract: An embodiment of the present invention may enable editing and deployment of software by including in an application container editable source code used to produce an application, and tools to edit and build the application, such as a code editor and a build tool to convert the source code to the executable application. The container may include an executable application which may execute in the environment on which the container is saved. A server in the container may control execution of the executable application and build the executable application. A remote user computer may communicate with the code editor to edit the source code, which in its updated version may be built to produce an updated version of the executable application. The server may stop execution of the existing executable application, and start execution of the updated version of the executable application.

Abstract: A computer-implemented method for automatically analyzing handwritten text to determine a mismatch between a purported writer and an actual writer is disclosed. The method comprises receiving two samples of digitized handwriting each allegedly created by one individual and received and entered into a digital system by another. The method further comprises performing a series of feature extractions to convert the samples into two vectors of extracted features; automatically clustering a set of vectors such that the first vector and the second vector are assigned to the same cluster among multiple clusters, based on vector similarity; and automatically determining that a same individual being associated with both the first and second samples indicates a heightened probability that the individual fraudulently created both samples. Finally, the method comprises automatically transmitting a message to flag additional samples of digitized handwriting entered into a digital system as possibly fraudulent.

Abstract: A computer-implemented system and method for tracking use of personally identifiable information by a computer asset of a firm. The method includes receiving one or more data elements associated with the computer asset, receiving an individual type associated with the one or more data elements, and determining whether the one or more data elements individually or as a combination constitute PII. In response to determining that the data elements constitute PII, the method includes determining whether enhanced data controls are necessary for the computer asset according to the one or more data elements that constitute the PII, determining a sensitivity of the PII, and recording the individual type, whether enhanced data controls are necessary, and the sensitivity of the PII in association with the computer asset in a database communicably coupled to the computer system.

Abstract: System comprises an application server for hosting a mobile application service; a mobile device having a mobile application for the mobile application service installed thereon; and a third party server. Application server is configured to: receive a log-in request for the mobile application service from the mobile device, where the log-in request includes device identifying information for the mobile device; transmit, to the third party server, a request for a status setting for the mobile application, wherein the request comprises the device identifying information for the mobile device, where the status setting comprises a plurality of bits, and where the third party server retrieves the status setting from a database based on the device identifying information for the mobile device; receive from the third party server, the status setting for the mobile application; and determine a risk rating for the log-in request based in part on the status setting for the mobile application.

Abstract: Domain specific knowledge base (KB) contains all concepts from domain and the semantic relations between concepts. The concepts and the semantic relations are extracted from an existing corpus of content for the domain. The World Wide Web Consortium (W3C) standard SKOS (Simple Knowledge Organization System) can be used and two types of semantic relations can be captured: hierarchal and associative. A Natural Language Processing (NLP) software engine can parse the input text to create a semantic knowledge graph, which is then mapped to a SKOS knowledge model. During the linguistic understanding of the text, relevant domain concepts are identified and connected by semantic links. Concepts automatically identified as most important in this domain can be promoted to another layer, referred to as “Topics.

Abstract: Software application for a digital display device determines, in real time, whether structures/objects of real property comply with applicable ordinances and permits. Mobile device app determines the street address for the property being inspected. User of the mobile device captures visual media of internal or external structure/object on the property. App detects the object in the visual media using computer vision-based image recognition. App calls back-end computer system to look up in real time applicable ordinances for the structure/object and/or whether there is an appropriate permit(s) for the structure/object. App generates and displays on the mobile device augmented visual media that visually indicates whether the detected structure/object is compliant or not.