Systems and methods for configuration vulnerability checking and remediation are provided. The systems provided herein identify risk based upon service indications of a particular configuration, such that automated risk analysis may be facilitated.

Systems and methods for configuration vulnerability checking and remediation are provided. The systems provided herein identify risk based upon service indications of a particular configuration, such that automated risk analysis may be facilitated.

The present disclosure relates to methods and systems for ingesting content from data feeds and to generate an enhanced output of relevant content for presentation to a user to facilitate analysis of the relevant content. Content is received from data feeds, and filtered to identify relevant content with respect to a particular context. The relevant content is then processed, e.g., using natural language processes, to extract entities involved, and to also identify particular activities detailed in the relevant content. Activity-mining is applied to the identified relevant data to classify and assigned activity tags to the extracted entity. Based on the extracted and identified information, an enhanced output is generated for presentation to facilitate research operations. The enhanced output may include overlaid graphical annotations, indicators, and graphical controls over the relevant articles to provide a means for updating a database based on the relevant content.

This application relates to apparatus and methods for generating preference profiles that may be used to rank search results. In some examples, a computing device obtains browsing session data and determines items that were engaged, such as items that were viewed or clicked. The computing device obtains item property data, such as product descriptions, for the items, and applies a dependency parser to the item property data to identify portions that include certain words, such as nouns or adjectives, which are then identified as attributes. The computing device generates attribute data identifying portions of the item property data as item attributes. In some examples, the computing device applies one or more machine learning algorithms to the session data and/or search query to identify item attributes. The computing device may generate a profile that includes the item attributes, and may rank search results based on the attribute data, among other uses.

The present disclosure describes a technology platform for creating and updating records of resources in a ledger. To create a record, a tenant organization may prepare a record to write to the ledger that may be flagged as temporary. Metadata may be added to the record, which flags the record as temporary. The metadata may comprise a unique code and an identification of a user that can approve the temporary record. The unique code and the identification may be sent, by the technology platform, to a device associated with one or more approving devices. Upon receiving the code and the identification of the transaction, the device may sign the unique code and invoke a routine based on the identification. The routine may fetch the temporary record. The device may compare the unique code to a code stored in the metadata of the temporary record. Upon valid verification of the unique code, the device may indicate authorization of the write. Based on the authorization, a proxy node associated with the technology platform may write a definitive record to the ledger based on the temporary record.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for selecting a text span from an input electronic document that answers an input question. One of the methods includes obtaining a respective first numeric representations of text spans in the input document; for each of the text spans: determining, for a segment that contains the text span, a question-aware segment vector, determining, for the question, a segment-aware question vector, and processing the first numeric representation of the text span, the question-aware segment vector, and the segment-aware question vector using a second feedforward neural network to generate a second numeric representation of the text span; for each unique text span in the plurality of text spans: determining an aggregate representation for the unique text span, and determining, from the aggregate representation, a final score for the unique text span; and selecting a unique text span.

In an approach for automatically ranking and routing data quality remediation tasks, a processor analyzes a data set ingested by a repository to produce a set of data quality problems. A processor computes a score for each data quality problem of the set of data quality problems. A processor identifies a route to send each data quality problem of the set of data quality problems. A processor exports each data quality problem according to the score and the route.

A query-based isolator comprising an observer, a collator and an extractor. The isolator reduces the database on which the query is run, to a new smaller, database on which the query can be performed, with the same result obtained on the smaller database, as that obtained on the original database.

Provided herein are systems, methods and computer readable media for classification and tagging of textual data. An example method may include accessing a corpus comprising a plurality of documents, each document having one or more labels indicative of services offered by a merchant, generating a query based on extracted features and the documents, generating a precision score for at least a portion of the generated query and selecting a subset of the generated queries based on an assigned precision score satisfying a precision score threshold, the selected subset of the generated queries configured to provide an indication of one or more labels to be applied to machine readable text. A second example method, utilized for tagging machine readable text with unknown labels, may include assigning a label to textual portions of the machine readable text based on results of the application of the queries.

A method for generating recommendations involves selecting a first platform message, making a first determination that the first platform message is potentially associated with a plurality of topics including a first topic and a second topic, obtaining additional information associated with the first platform message including at least one of information about an account that authored the first platform message and information about third party accounts engaging with the first platform message, making a second determining that the first platform message is associated with the first topic using the plurality of topics and at least a portion of the additional information, wherein the first topic is an initial classification of the first platform message, generating a recommendation for at least one account based on the second determination, and providing the recommendation to at least one account.