A system, method, and computer program product are disclosed. The method includes loading a first set of data as an initial matrix and determining a truncated singular value decomposition (SVD) of the initial matrix. The method also includes loading a second set of data as a new matrix, generating a first projection matrix, which approximates k leading left singular vectors of the updated matrix, and generating a second projection matrix, which approximates k leading right singular vectors of the updated matrix. Further, the method includes determining based on the initial matrix, the new matrix, the SVD of the existing matrix, and the first or second projection matrix, an approximate truncated SVD of the updated matrix.

Systems and methods that can provide verifications and grades corresponding to items represented within ecommerce platforms such as online resume generation, online product marketplace, and online social media platforms. Evaluations of items such as skills, products, users, topics, and characteristics of users and items, contribute to verifications and grades that can be displayed in a user-friendly and understandable manner, employing graphic indicators. Contributions to the verifications and grades can be weighted according to grader profiles and item classification.

Methods and apparatus related to determining reply content for a reply to an electronic communication. Some implementations are directed generally toward analyzing a corpus of electronic communications to determine relationships between one or more original message features of “original” messages of electronic communications and reply content that is included in “reply” messages of those electronic communications. Some implementations are directed generally toward providing reply text to include in a reply to a communication based on determined relationships between one or more message features of the communication and the reply text.

Described herein is a regulatory parser that downloads and efficiently processes regulatory documents. The regulatory documents may be from different sources and may have different formats. The regulatory parser parses all of the text in the regulatory documents and converts into a predetermined, single format for downstream applications. The text is organized and stored in a structured tree, organized into one or more hierarchies with nodes storing segments of text from a regulatory document. In some embodiments, each node in the regulatory tree may represent a segment of text. Partitioning the text of a regulatory document into segments of text may make the storage and querying of the regulatory documents more manageable. The organization and structure of the structured tree may reduce the times and resources needed for accessing and searching for a regulatory citation. The structured tree may allow a user to manipulate a regulatory document or text.

A method of integrating data across multiple data stores is provided. The method includes ingesting diverse data from multiple data sources and reconciling the ingested diverse data by updating semantic models based on the ingested diverse data. The method further includes storing the ingested diverse data based on one or more classification of the data sources according to the semantic models and automatically generating scalable service endpoints that are semantically consistent according to the classification of the data sources. The generated scalable service endpoints are application programming interfaces. The method also includes determining a protocol based on the scalable service endpoints in response to receiving a call from the one or more recipient systems and responding to the call from the one or more recipient systems by providing data in the classification of the data sources.

Improved technological solutions are introduced for providing a secure and effective and enhanced clustering/grouping solution that is useful, for example, in an online dating forum as well as any number of other industries. The ability to attend live events in person or remotely is coupled with presence location and automatic verification of user devices and identities. This allows secured communication between participants without having to disclose actual contact information of the participants or their device addresses. An improved algorithm that groups members/items effectively based on a variety of matching criteria, with lowered possibilities of errors and more efficient use of processing power, is now introduced.

Techniques are described herein for training and evaluating machine learning (ML) models for document processing computing applications based on in-domain and out-of-domain characteristics. In some embodiments, an ML system is configured to form feature vectors by mapping unknown tokens to known tokens within a domain based, at least in part, on out-of-domain characteristics. In other embodiments, the ML system is configured to map the unknown tokens to an aggregate vector representation based on the out-of-domain characteristics. The ML system may use the feature vectors to train ML models and/or estimate unknown labels for the new documents.

A text classification method includes: obtaining a target text and an associated text corresponding to the target text; performing feature extraction on the target text and the associated text to obtain feature information, the feature information including one or more features; processing the feature information by using an attention mechanism to obtain one or more attention weights respectively corresponding to the one or more features, an attention weight indicating importance of the corresponding feature for the target text and the associated text; and obtaining a class detection result and result interpretation information corresponding to the target text based on the feature information and the one or more attention weights, the class detection result comprising a class distribution probability corresponding to the target text, and the result interpretation information describing impact of the one or more features on the class detection result.

A system for voice recognition in autonomous flight of an electric aircraft that includes a computing device communicatively connected to the electric aircraft configured to receive at least a voice datum from a remote device, wherein the voice datum is configured to include at least an expression datum, generate, using a first machine-learning process, a transcription datum as a function of the at least a voice datum, extract at least a query as a function of the transcription datum, generate, using a second machine-learning process, a communication output as a function of the at least a query, and adjust a flight plan as a function of the communication output.

State of art techniques that utilize spatial association based Table structure Recognition (TSR) have limitation in selecting minimal but most informative word pairs to generate digital table representation. Embodiments herein provide a method and system for TSR from an table image via deep spatial association of words using optimal number of word pairs, analyzed by a single classifier to determine word association. The optimal number of word pairs are identified by utilizing immediate left neighbors and immediate top neighbors approach followed redundant word pair elimination, thus enabling accurate capture of structural feature of even complex table images via minimal word pairs. The reduced number of word pairs in combination with the single classifier trained to determine the word associations into classes comprising as same cell, same row, same column and unrelated, provides TSR pipeline with reduced computational complexity, consuming less resources still generating more accurate digital representation of complex tables.