Abstract: The present technology proposes techniques for ensuring globally consistent transactions. This technology may allow distributed systems to ensure the causal order of read and write transactions across different partitions of a distributed database. By assigning causally generated timestamps to the transactions based on one or more globally coherent time services, the timestamps can be used to preserve and represent the causal order of the transactions in the distributed system. In this regard, certain transactions may wait for a period of time after choosing a timestamp in order to delay the start of any second transaction that might depend on it. The wait may ensure that the effects of the first transaction are not made visible until its timestamp is guaranteed to be in the past. This may ensure that a consistent snapshot of the distributed database can be determined for any past timestamp.

Abstract: The Variable Data Source Dynamic and Automatic Ingestion and Auditing Platform Apparatuses, Methods and Systems (“DIAP”) transforms file upload request, external data request, and analytics request inputs via DIAP components into clean data, metadata data sets, visualization module output, and audit notification outputs. A data ingest request is obtained via a user interface. A data file to ingest is obtained and processed to generate a clean file. A database table with a unique name is created and data in the clean file loaded into the database table. A metadata data set identifier is generated. Table columns from the database table to include into the metadata data set are determined, and the metadata data set is generated. The metadata data set links columns from the database table to analytics engine UI elements, and columns are associated with audit trail data via the metadata data set identifier.

Abstract: A method and system for training a machine-learning algorithm (MLA), including first and second machine-learning (ML) models to rank digital documents at a digital platform. The method comprises: receiving first historical data of past searches conducted by the given user over a given past period; receiving second historical data, a given portion of the second historical data including data of past searches conducted by the given user over a given past user session; jointly training both the first and second ML models to rank the in-use digital documents, the training comprising: training, based on the first historical data, the first ML model to generate a vector representation of the first historical data; and training, based on the vector representation of the first historical data and the second historical data, the second ML model to determine a respective likelihood value of the given user interacting with a given in-use digital document.

Abstract: An example operation may include one or more of executing queries on one or more external data stores to retrieve domain data of one or more ranked lists of assets and variables corresponding to the domain data, generating a plurality of feature groups based on the retrieved domain data and variables, wherein the plurality of feature groups correspond to a plurality of features used to generate the one or more ranked lists, converting the plurality of features groups into a plurality of values via execution of an optimization engine, transforming the plurality of values into a plurality of sentences describing the plurality of feature groups, and displaying the plurality of sentences via a user interface.

Abstract: Disclosed herein are system, method, and computer program product embodiments for extracting data to stream to a user interface using a client library and configuration file. An embodiment operates by receiving the configuration file from a replication management system (RMS). The embodiment accesses a RMS pod using the client library. The embodiment retrieves a list of tables in a repository using the client library. The embodiment chooses at least one table from the list of tables. The embodiment downloads data from the at least one table. The embodiment exports the data in a readable file format. The embodiment then streams the exported data to the UI.

Abstract: 1000 MORE is a digital political marketplace that centralizes all civic engagement for constituents, advocacy organizations and elected officials. It generates information about bills coming up for a vote, elected officials, and advocacy efforts, then provides action options including calls, emails, connecting via social media and crowdfunding. 1000 MORE provides constituent users with information about how their elected officials and candidates align with their interests based on their usage of the platform. With that information in hand, constituents can engage with candidates through phone, email, social media or donations. Furthermore, 1000 MORE uses that information to build a hyper personalized voter guide for constituents. It also gamifies civic engagement with a scoring system and options to connect with other users. Advocacy organizations have an interface where they can connect with constituents and crowdfund.

Abstract: A computer-implemented method, system and computer program product for identifying equivalent technical terms. A deep learning model is trained to identify equivalent technical terms. The deep learning model is then applied to a new document. The sentences of the document are analyzed to identify technical terms. Text is then analyzed surrounding the technical term identified in the document to determine the meaning of such text. A glossary list is then reviewed to determine if the identified meaning of the analyzed text matches a meaning/concept in the glossary list linked to a technical term. In response to determining that the meaning of the analyzed text matches a meaning/concept in the glossary list linked to an equivalent technical term, the technical term in the document is annotated with the equivalent technical term. In this manner, non-standard equivalent technical terms in different documents with the same meaning/concept are able to be identified.

Abstract: A method, a computer system, a server, and a non-transitory computer-readable storage medium for providing a search service are provided. The method of providing the search service includes: executing the search service provided through a chatroom associated with a messenger application; and, based on a first search term input for the search service, displaying, on a search entry area, first search results corresponding to the first search term and at least one autocomplete search term of the first search term.

Abstract: A computing system is provided, including non-volatile storage storing a reactive database including a plurality of database entities. The computing system may further include a processor configured to, via a reactive database application program interface (API), receive a first standing query registration input including a first standing query. The first standing query may include a first update condition and may be associated with a first database entity. The processor may be further configured to store the first standing query in the non-volatile storage. The processor may be further configured to write data to the reactive database and determine that the first update condition is satisfied by the written data. In response to determining that the first update condition is satisfied, the processor may be further configured to execute the first standing query to perform a first state change at the first database entity of the plurality of database entities.

Abstract: A data protection system utilizes certain supervised learning processes to implement a granular level prioritized protection scheme for critical data based on decision tree processing. This process provides intelligent backup protection not only at the asset or sub-asset level, but also at the molecular level to meet the desired level of priority-based operation. Such embodiments overcome disadvantages of current systems that provide this level protection only upon management by an administrator by providing automated intelligence to provide granular protection at any appropriate data object level.

Abstract: Embodiments provide for predicted data use obligation matching using data differentiators. Example embodiments retrieve a cross-link relationship graph structure from a data repository, where the cross-link relationship graph structure includes a plurality of cross-link relationship graph nodes connected by a plurality of cross-link relationship graph edges. Each cross-link relationship graph node is associated with a unique logical data record set identifier of a plurality of logical data record set identifiers associated with a dataset identifier. For each unique logical data record set identifier, the cross-link relationship graph structure is traversed. Based at least in part on a separation measure associated with each cross-link relationship of one or more cross-link relationships associated with the unique logical data record set identifier, one or more data use obligation scores for the unique logical data record set identifier is generated.

Abstract: The present disclosure relates to computer-implemented methods, software, and systems for processing hierarchies of data. A first changeable version of a current hierarchy of nodes is created to refer to a current stable version and to a first set of new relations associated with changes in a first set of relations between entities in the current stable version is response to a received first instruction. A second instruction to adjust the current stable version is received from a second user. In response to receiving the second instruction, a second changeable version of the current hierarchy of nodes is created. The second changeable version refers to the first changeable version and to a second set of new relations associated with changes in a second set of relations between entities in the first changeable version. A new stable version of a new current hierarchy of nodes is generated.

Abstract: Methods and systems for simplifying data collected from assets are provided. An example method involves receiving a simplified set of data at a server. The simplified set of data is generated by application of a dataset simplification algorithm on raw data obtained from a data source at an asset upon a determination that a recently obtained point in the raw data differed from a corresponding predicted point predicted by extrapolation based on previously saved points included in one or more previously generated simplified sets of data by an amount of extrapolation error that is limited by an upper bound that is fixed as the raw data is collected over time. The method further involves receiving a request for a status of the asset and extrapolating a status of the asset based on the simplified set of data in response to the request.

Abstract: Embodiments described herein are directed to detecting data inconsistencies within a distributed database and identifying the cause thereof. For example, lineage events are emitted from different components of the distributed system that operate on various data files. A consistency checking engine analyzes these events and detects inconsistencies with respect to the data files. The embodiments described herein checks the integrity of the database and assists in understanding the root cause in case of a corruption. Moreover, it provides the timeline for the corruption and whether it is repairable or not. These properties enable determining the right time to restore the customer's database or the right set of actions to repair the corruption. In case of repairable corruption, the correct compensating repair actions may be applied.

Abstract: Embodiments as disclosed herein provide for a system and method that can manage indexing for search index partitions in a computerized search system in an automated, efficient, and intelligent manner. In particular, a search index may be partitioned. One or more index partitions may be specifically indicated as one or more reserved partitions configured to handle indexing requests associated with processing a very large amount of information. When an indexing request is received that requests indexing of a very large amount of information, the indexing request may be processed for a reserved index partition that is reserved for indexing objects associated with a very large amount of information; otherwise, the request may be processed for another index partition.

Abstract: Systems and methods for providing personalized answers to a user's query using a learned user vocabulary. A natural-language user interface (NLUI) application tracks input terms in user queries and generates responses that incorporate those input terms. The NLUI application may modify stored response templates or may modify a response generated based on stored response templates, by replacing a template term with an input term that has a common definition.

Abstract: A computer-implemented system for organizing data migration is disclosed. The computer-implemented system includes a receiving module to receive a plurality of data as an input from a user, a recommendation module generates a plurality of recommendations by processing on the received input using an artificial intelligence model. The plurality of recommendations includes a plurality of migration plans. A cloud migration module receives a plurality of inputs based on the plurality of migration plans and automatically generate a landing zone pertaining to a first migration wave, a post-migration phase module perform a continuous improvement loop after each phase of the first migration wave, fine-tune the continuous improvement loop for subsequent migration waves, and continuously analyze a predefined cloud platform environment to identify areas of improvement, a chatbot module provides on-demand support to the user during and after the migration.

Abstract: A method, computer system, and a computer program for conducting a conversational search. In one embodiment, the method includes monitoring a dialogue involving at least one user and capturing user utterances provided during the dialogue. These user utterances are then analyzed and classified according to the context of the dialogue. The dialogue is intervened upon the determination that a user needs additional information and/or upon execution of an action on behalf of the user and based on the plurality of user utterances and context. The Required information may be provided back to the user using Documentation Recommendation Module. The Documentation Recommendation Module determines a valid resource recommendation as determined by a combination of the context and a resource that includes additional information.

Abstract: Examples of the present disclosure describe systems and methods for enterprise search that leverage periodically updated user context of an enterprise user for intent understanding and treat a search session as a dialog between the user and a digital assistant to allow multi-modal interaction. For example, a query input by the user may be received from a client application having search functionality and an integrated assistant. A current state of the user context may be leveraged to understand the query. Based on the understanding, one or more responsive entities may be retrieved from an enterprise search index as results. Based on the results, a response may be generated that includes the results and a prompt to cause the user to further refine the query and/or provide feedback. The response may be provided to the client application for output as part of a search session dialog between the user and assistant.

Abstract: Disclosed is a search result display device (1) comprising: a regard prediction unit (12) configured to predict, from a dialogue between a customer and a service person, a regard of the customer; a keyword extraction unit (17) configured to extract a keyword from the regard; and a display controller (13) configured to cause a display (14) to display the dialogue and a search result obtained from the database (21) with the keyword as a search query, wherein when a string has been designated by the service person, the display controller (13) causes the display (14) to display a search result obtained from the database (21) using a search query that incorporates the string, until a search result automatic update instruction is given by the service person.