Abstract: Methods, apparatus and computer program product that may include receiving, by one or more servers of a group-based communication platform and from a client of a first user with administrative privileges and associated with a first organization, a request to generate a shared communication channel on the group-based communication platform. A shared communication channel may be generated based on the request. A second request may be received by the one or more servers to provide at least one second user associated with a second organization access to the shared communication channel. Access may be provided to the second user. A message communication may be rendered in a shared communication channel interface associated with the shared communication channel with a graphical indicator that indicates the message communication is associated with the first organization.

Abstract: Improved artificial intelligence computer systems actively and/or passively provide end-users with information from firm data systems to help the end-user perform the end-user's job functions. In a passive implementation, the system can prioritize emails for a user, craft consistent responses to multiple email inquiries on the same topic, and/or craft responses whose content is drawn from a library of electronic documents. In an active implementation, the system comprises AI agents associated with individual databases of the system, where the AI agents are tuned to retrieve data from their associated database in response to a query from the end-user.

Abstract: At least one table included in first content may be determined. The at least one table includes a first plurality of rows and a first plurality of columns. It may be determined that a first term indicative of a personal name is included in a first row of the first plurality of rows and a first column of the first plurality of columns. A second row of the first plurality of rows that includes at least a first personal name in the first column and a first item of personal identifying information in a second column of the first plurality of columns may be identified. First data indicative of the first personal name and the first item of personal identifying information may be extracted. The first data may be added to a first profile associated with the first personal name.

Abstract: Disclosed are systems and methods for XBRL tag outlier detection. In some embodiments, the method includes the steps of: receiving a first set of XBRL data records; generating a second set of XBRL data records based upon a subset of the first set of XBRL data records; training a machine learning model using the first set of XBRL data records and the second set of XBRL data records; receiving an XBRL document associated with one or more assigned XBRL tags; and analyzing the XBRL document using the trained machine learning model to identify a set of outlier XBRL tags in the one or more assigned XBRL tags.

Abstract: A request is received associated with reviewing content. As part of the request, one or more conditions are received and the content is analyzed to identify a first field of interest and a second field of interest. The first field of interest and the second field of interest represent fields of interest associated with the review of the content. At least one of the first field of interest or the second field of interest may not satisfy the one or more conditions and the content, or a portion thereof, may be sent for review.

Abstract: A method for classifying organizations involves obtaining, for an unknown organization, transactional data representing a multitude of transactions. The transactional data comprises a descriptive text for each of the multitude of transactions. The method further involves processing the descriptive text for each of the multitude of transactions to obtain one vector representing the unknown organization, categorizing the unknown organization using a classifier applied to the vector, and identifying a software service for the unknown organization, according to the categorization.

Abstract: Entity resolution (i.e., record linkage) involves the analysis/discovering of datasets that refer to the same real world entity. Analysis typically involves transformation and comparison of different fields of the dataset followed by the application of often domain/data specific logic for determining datasets that refer to the same real world entity (e.g., person). Consider, a bulk mailing of product catalogs to potential customers. Some individuals may have numerous public records that identify the individual differently. Illustratively, several records associated with Jane Doe at her current home address may exist: one record with her name listed as J. Doe, a second record as Jane H. Doe, a third record as Doe, Jane, and a fourth record as Jan Doe (a misspelling). Conceivably, the bulk mailing could unwittingly send multiple catalogs to Jane Doe at her current address, one for each name variation. The entity resolution process described herein can overcome such problems.

Abstract: A log-to-metrics transformation system includes a log-to-metrics application executing on a processor. The log-to-metrics transformation system receives a format associated with machine data, and further receives, via a first graphical control, a first set of metric identifiers corresponding to a first set of metrics associated with the machine data. The log-to-metrics transformation system generates a first set of mappings between the first set of metric identifiers and a first set of field values included in the machine data. The log-to-metrics transformation system stores the first set of mappings and an association with the format of the machine data. The log-to-metrics transformation system, based on the first set of mappings, causes the first set of field values to be extracted from the machine data. Further, a first metric included in the first set of metrics is determined based on at least a portion of the first set of field values.

Abstract: Search assistance personalized to a user, may be afforded by combining the application of scoring functions, with the training a Machine Learning (ML) model based upon feedback from that user. A plurality of scoring functions are applied to query results to calculate a plurality of score vectors. The ML model is then applied to generate a ranked list of vectors. Feedback from the user, is incorporated to develop an evolving memory. The feedback may be explicit, or may be implicit—e.g., based upon user selection of particular score vector(s) from the list or based upon user selection of particular query results corresponding to the score vectors. Embodiments may enhance relevance of search assistance by removing past feedback from the evolving memory that is used to retrain the ML model. Embodiments can provide assistance to search text corpuses utilizing scoring functions considering frequency of occurrence of particular words or terms.

Abstract: Performing, by a low-latency data access and analysis system, automatic grammar switching includes, in response to obtaining data indicating a request to switch from using a first defined grammar to using a second defined grammar, wherein the request includes data representing a first resolved-request generated for a first input string using the first defined grammar, generating, using the second defined grammar, a second resolved-request for the first input string, automatically generating a data-query in accordance with the second resolved-request, and outputting output data including results data obtained by executing the data-query.

Abstract: Methods, apparatuses, and systems for intention based search techniques are described herein. An example method comprises receiving data indicative of an intent of a user to perform an action via at least one application, the data comprising a description of the action that is input via a client device application on a client device, identifying, by the computing device, the at least one application based on a comparison of the description of the action and one or more records, the one or more records being indicative of prior intents of one or more users to perform actions and indicative of at least one selection by the one or more users to perform the actions with a selected application, and providing, by the computing device, output to the client device to enable performance of the action via the at least one application.

Abstract: An illustrative embodiment includes a method for post-retrieval query performance prediction using hybrid document-passage information. The method includes: obtaining a set of documents responsive to a specific query; extracting document-level information regarding respective documents within the set; extracting passage-level information regarding respective passages of documents within the set; and estimating a likelihood that the set of documents includes relevant information to the specific query using both the document-level information and the passage-level information.

Abstract: A computer retrieves data from a database. The computer retrieves a Machine Learning (ML) model trained to generate database queries. The computer applies the ML model to generate a primary database query based, at least in part, on a user inquiry available to the computer. The computer retrieves the primary database query, an initial set of data from a database available to the computer. The computer, in response to retrieving the initial set of data, receives feedback assessing the initial set of data. The computer, in response to receiving the feedback, applies a Natural Language Processing (NLP) model to identify query adjustment content within the feedback. The computer revises the primary database query based, at least in part, on the model adjustment content, to generate a secondary database query. The computer retrieves using the secondary database query, a secondary set of data from the database.

Abstract: The present inventive subject matter provides systems, methods, software, and data structures for patent mapping, storage, and searching. Some such embodiments include mapping patent documents, claims, and claim limitations. Some further embodiments provide for searching a universe of patent documents by patent document, claim, limitation, class, element, or concept.

Abstract: Search guidance includes generating user interface data for at least a portion of a user interface including a user input element, a data-analytics request construct card, and a data-analytics guidance portion. The data-analytics request construct card includes text describing usage of a data-analytics request construct card grammatical function. The user interface data is output for presentation to a user. Data-analytic request construct card data expressing usage intent is received and updated user interface data is generated. The updated user interface data corresponds to an updated user input element in accordance with the data-analytic request construct card data and an updated data-analytics guidance portion in accordance with the data-analytic request construct card data. The updated user interface data is output. Resolved-request data is generated in accordance with the data-analytic request construct card data.

Abstract: Disclosed are system and methods for processing and storing data files, using a data edge file format. The data edge file format separates information about what symbols are in a data file and information about the corresponding location of those symbols in the data file. Examples convert a source file comprising symbols into a data edge index having a manifest portion, a symbol portion, and a locality portion. The symbol portion contains a sorted unique set of symbols from the source file, and the locality portion contains a plurality of location values referencing the symbol portion. Examples include normalizing structured data from the source file by modifying the locality manifest portion of the data edge file to include a description of at least one nonexistent column empty locality value at a respective position within the locality file representing an omission of data at an associated position in the source file.

Abstract: Systems, methods, and media for real-time processing of event-based streaming with NoSQL databases are provided. For example, disclosed embodiments may include receiving an event associated with an update to an entry in a first database. Also, disclose embodiments may include identifying, based on the event, relevant data in the first database associated with the update. Further, disclose embodiments may include generating a plurality of queries to the first database to request the identified relevant data. Disclose embodiments may also include receiving, in response to the plurality of queries, raw data from the first database. Additionally, disclose embodiments may include processing the raw data to be compatible with a second database. Disclose embodiments may also include storing the processed raw data in the second database. And, disclosed embodiments may include receiving data requests for the second database to distribute the processed data to at least one computer terminal.

Abstract: A computer-implemented communications method is discussed. The method includes receiving a typed user input in a texting conversation on an electronic communication channel between two or more users of electronic communications devices; analyzing the user input to identify whether the user input contains a reserved word for triggering a search; submitting a search query received in association with the reserved word to a search engine, if the user input contains a reserved word; receiving one or more search results from the search engine; and providing, in the electronic communication channel for incorporation into the texting conversation, at least one of the one or more search results.

Abstract: Adaptive field-level matching is described. A system identifies first elements in a field of a prospective record for a database, and second elements in the field of a candidate record, in the database, for matching the prospective record. The system identifies features corresponding to any of the first elements that are identical to any of the second elements, any of the first elements that are absent from the second elements, and any of the second elements that are absent from the first elements. A machine-learning model uses the features to determine a field match score for the candidate record's field. Another machine-learning model weighs the field match score and weighs another field match score for another field of the candidate record to determine a record match score for the candidate record. If the record match score satisfies a threshold, the system identifies the candidate record as matching the prospective record.

Abstract: Systems, methods, and non-transitory computer-readable media can be configured to determine a page embedding for each page in a sequence of pages visited by a user. A pooled page embedding can be determined based on the page embeddings for the sequence of pages visited by the user. One or more page recommendations for the user can be determined based at least in part on the pooled page embedding.