Abstract: Systems and methods for protection of data across multiple users and devices are disclosed. According to one embodiment, in privacy server comprising at least one computer processor, a method for protection of data across multiple users and devices may include: (1) receiving, from a first user device, a data sharing permission for the first user device and a data sharing permission for a second user device, the first user device and the second user device associated with the same user; (2) provisioning the data sharing permission for the second user device; and (3) communicating the provisioned data sharing permission to the second user device, wherein the second user device shares data with the first user device according to the provisioned data sharing permission.

Abstract: A method and system for operating an application program interface-based content management system. The method and system each comprises: communicating, by an application that is based on a microservices architecture, with a user interface via content APIs that provide for content creation, content modification, content storage, and content retrieval; storing, by the application, within a relational database, relational data, identification data, and access control data; storing, by the application, within a content store that comprises an object storage database, content as objects in buckets of the object storage database; communicating, by a search engine, with the application via search APIs that provide for a full text-based search of the object storage database; storing, by the search engine, within memory of the search engine, metadata that corresponds to the data; and storing, by the search engine, within the memory, reference data that corresponds to the data.

Abstract: In some aspects, the techniques described herein relate to a method including: providing one or more curation content machine learning models, wherein the one or more curation content machine learning models are configured to classify a textual review into a plurality of classifications, and wherein the plurality of classifications have been assigned respective relative weights; receiving, at a collaboration service, a user review of a travel objective from a user of the collaboration service; providing the review as an input feature dataset to the one or more curation content machine learning models; receiving, as output of the one or more curation content machine learning models, a plurality of classifications of the user review; and aggregating, by the collaboration service, a relative value score based on the assigned relative weight of the plurality of classifications of the user review.

Abstract: A method and a system for performing a search in a dataset in a mainframe session are disclosed. The method includes receiving at least one keyword associated with at least one query. The method includes identifying at least one from among at least one step containing the at least one keyword and at least one paragraph containing the at least one keyword based on the at least one query. The method includes tagging at least one identifier to at least one from among the at least one identified step and the at least one identified paragraph. Next, the method includes verifying the at least one tagged identifier. Thereafter, the method includes displaying at least one from among the at least one identified step and the at least one identified paragraph.

Abstract: Embodiments use quantum conditional logic in the Quantum Phase Estimation Algorithm (QPEA) to compute eigenvalues prior to inversion. Embodiments estimate the eigenvalues of a unitary, U=eiÂt, generated by a N×N Hermitian matrix Â. The binary representations of the n-bit estimations of eigenvalues of  may be encoded in these states: |?i=|b1b2 . . . bn; ?i is an estimation of the i-th eigenvalue, excluding degeneracy, and .b1b2 . . . bn is its binary representation. To perform the eigenvalue inversion, an n-qubit controlled Ry rotation with angle ?i/2(n?1) conditioned on seeing |b1b2 . . . bn is applied for each possible n-bit binary string b1b2 . . . bn (2n values). The overall unitary is called a “uniformly controlled Ry rotation” in literature.

Abstract: Systems and methods for enhanced organizational transparency using a linked activity chain in a ledger are disclosed. In one embodiment, a method may include (1) a back end for an organization comprising at least one computer processor receiving a first communication from a first entity comprising a first customer interaction with the first entity; (2) the back end writing the first communication to a ledger for the organization as a first block in a linked activity chain; (3) the back end receiving a second communication from a second entity comprising a second customer second activity with the second entity; (4) the back end writing the second communication to the ledger for the organization as a second block in the linked activity chain; (5) the back end calculating a summary score for the customer based on the blocks in the linked activity chain.

Abstract: A method and system for generating cluster level explanations for an input data having limited or special values are disclosed. The method includes obtaining an input data set and a clustering stopping criteria, the input data set including multiple features, and each of the features having multiple feature values; performing features decomposition on the input data; performing correlation analysis based on the features decomposition and a correlation threshold value; grouping the features having different feature values into multiple clusters; training a model based on the obtained input data; obtaining a target input data to be tested and a number of cores; grouping the number of cores into multiple clusters; and computing explanations at a cluster level.

Abstract: In one example, a storage medium with program instructions to deploy immutable-image software to retail branch devices is disclosed. The operations include accessing a user-interface change request to initiate an event on a remote computer system. The event is a deployment of immutable branch-image software to alter or reimage existing software on the remote computer system. The operations include authenticating an identity of a user interface operator, publishing an event message (preload and build) on a messaging databus. An agent communicating with the remote computer system subscribes to the messaging databus.

Abstract: In one example, a storage medium with program instructions to deploy immutable-image software to retail branch devices is disclosed. The operations include accessing a change request from a user interface to initiate an event on a remote computer system. The event is a deployment of immutable branch-image software to alter or reimage existing software stored or executed on the remote computer system. The operations include validating that the deployment of the immutable branch-image software is required on the remote branch computer system and generating a new partition in a memory of the remote branch computer system. The operations also include retrieving the immutable branch-image software via a secure network socket in response to the event message, installing the immutable branch-image software in the new partition and transferring operation of the remote branch computer system from an original partition of the memory to the new partition.

Abstract: A method for using a large language model to generate executable code for workflow execution in a manner that integrates user feedback and adjusts the workflow as needed while preserving data privacy is provided. The method includes: receiving first information that relates to a workflow context, second information that relates to at least one application programming interface (API), and third information that relates to a code generation request; using the received information to generate a lecture, and transmitting the lecture to a language model; receiving a user query that relates to performing a task, and transmitting the query to the language model; receiving a workflow that is automatically generated by the language model based on the lecture and the query; and executing the workflow in order to generate an output that is responsive to the query.

Abstract: A method and system for using a configuration-based framework for testing an application programming interface (API) are provided. The method includes receiving identification information about one or more APIs to be tested; defining, based on the first information, at least two API endpoints and one or more dependencies to be tested; retrieving an authentication model to be used for accessing the APIs; generating a testing plan based on the API endpoints, the dependencies, and the authentication model; executing a test of the APIs based on the testing plan; and displaying at least one result of the executed test on a graphical user interface (GUI).

Abstract: Methods and systems for performing a combinatorial optimization task are provided. The method includes: receiving a first set of data items and a second set of data items; dividing the second set of data items into a first subset and a second subset; generating, based on the first subset, a first set of subset sums, and storing the first set of subset sums as a list; generating, based on the second subset, a second set of subset sums, and storing the second set of subset sums as a hash-map in conjunction with a corresponding hash function; and detecting, based on the first set of data items, the list, and the hash-map, at least one match between a subset sum that corresponds to the second set of data items and a subset sum that corresponds to the first set of data items.

Abstract: Methods and systems for detecting attempted manipulation of a machine learning model via explanation poisoning are provided. The method includes: computing explanations based on outputs of the model that include information that relates to features that affect the output of the model with respect to the first data point; assigning labels to the explanations based on the features; generating an explanation ensemble that resides in an N-dimensional space, N being equal to a number of assigned labels plus one; determining a region within the N-dimensional space for which a subsequent introduction of data causes a subsequent explanation that does not relate to the features; and when the additional data is introduced to the determined region, generating an alert message for notifying a user that a likelihood of adverse manipulation of the model is high based on the additional data.

Abstract: A method for automatically classifying and tagging natural language data is disclosed. The method includes receiving, via an application programming interface, requests from various sources, each of the requests including raw data in a natural language format; converting the raw data into structured data sets; determining, by using a model, a metadata output for each of the requests based on the corresponding structured data sets; appending the metadata output to the corresponding requests; determining an action for each of the requests based on the corresponding metadata output; and automatically initiating the action.

Abstract: A method, system, and computer-readable storage medium for providing actionable corrections to, and code refactoring of, executable code. The method comprising: utilizing input to generate a machine learning model that analyzes quantitative information and qualitative information of an execution of an application code; executing the application code within a runtime environment of the application code, either of which incorporates a trace; during the executing, utilizing the trace to collect, at least one metric and/or at least one event; during the executing, ascertaining, by the machine learning model, the quantitative information and the qualitative information, by analyzing the at least one metric and/or the at least one event; and determining, by the machine learning model, at least one correction to the application code and/or at least one refactoring of the application code, by analyzing the quantitative information and the qualitative information.

Abstract: A method for using encryption and tokenization to protect confidential data that is stored in a public cloud database is provided. The method includes: receiving a first data set; tokenizing the first data set; obtaining a first token for at least one attribute of the first data set; encrypting an original value of the attribute and the first data set; storing each of the original value of the at least one attribute, the encrypted value of the at least one attribute, and the first token in a first memory; storing each of the first token and the encrypted first data set in a second memory; and storing the tokenized first data set in a third memory that is hosted on a public cloud server.

Abstract: A method may include a centralized recommendation engine computer program receiving a request for content to display on a mobile electronic device from an ad framework, and requesting offers for the customer based on the customer context from an offer interface platform; the offer interface platform querying a plurality of offer providers for offers, receiving a plurality of ranked offers and an offer identifier for each ranked offer from each of the plurality of offer providers and caching the plurality of ranked offers and an offer identifier for each ranked offer; the centralized recommendation engine computer program receiving the offer identifiers for the ranked offers and providing the offer identifiers for the ranked offers to the ad framework. The ad framework requests content for the ranked offers associated with the offer identifiers from the offer interface platform and generates a webpage with the content in the spaces.

Abstract: A method for providing portfolio deviation analytics to facilitate collateral management is disclosed. The method includes retrieving trade data from a source based on a predetermined schedule, the trade data including transaction information and valuations information; retrieving reference data from a reference data hub; parsing the reference data to identify portfolios and corresponding parameters; identifying a deviation amount for each of the portfolios based on the corresponding trade data and the corresponding parameters; determining a resolution action for each of the portfolios based on the corresponding deviation amount; and automatically initiating the resolution action.

Abstract: A method for facilitating recursive data refinement with self-documentation is provided. The method includes receiving, via a data ingestion component, raw data that is published from a networked repository; generating a conformed data set from the raw data based on a conformation parameter; retrieving, via a communication interface, a feature configuration; generating, in real-time, a featurized data set from the conformed data set based on the feature configuration; and publishing the featurized data set to the data ingestion component for further processing.

Abstract: A method and system for generating keywords that distinguish a group of selected documents from a larger corpus. The method includes: receiving a corpus that includes a plurality of documents; selecting from the corpus, based on at least one predetermined criterion, a group of the documents; determining a first Inverse Document Frequency (IDF) score for each word in a vocabulary of the group with respect to the corpus; determining a second IDF score for each word in the vocabulary of the group with respect to the group; generating based on the first IDF score and the second IDF score, a Group Frequency Inverse Document Frequency (GFIDF) score for each word in the vocabulary of the group; and assigning based on the generated GFIDF score for each word in the vocabulary of the group, at least one keyword.