Provided are a video title generation method, an electronic device and a storage medium, which relate to a technical field of video, and in particular to a technical field of short video. The method includes: obtaining a plurality of pieces of optional text information, for a first video file; determining central text information, from the plurality of pieces of optional text information, the central text information being optional text information with the highest similarity to content of the first video file; and determining the central text information as a title of the first video file. That is, an interest point in an original video file can be determined according to user's interactive behavior data on the original video file, and the original video file can be clipped based on the interest point to obtain a plurality of clipped video files, namely, short videos.

A method for training a language model based on various word vectors, a device and a medium, which relate to the field of natural language processing technologies in artificial intelligence, are disclosed. An implementation includes inputting a first sample text language material including a first word mask into the language model, and outputting a context vector of the first word mask via the language model; acquiring a first probability distribution matrix of the first word mask based on the context vector of the first word mask and a first word vector parameter matrix, and a second probability distribution matrix of the first word mask based on the context vector of the first word mask and a second word vector parameter matrix; and training the language model based on a word vector corresponding to the first word mask.

A method for training a language model based on various word vectors, a device and a medium, which relate to the field of natural language processing technologies in artificial intelligence, are disclosed. An implementation includes inputting a first sample text language material including a first word mask into the language model, and outputting a context vector of the first word mask via the language model; acquiring a first probability distribution matrix of the first word mask based on the context vector of the first word mask and a first word vector parameter matrix, and a second probability distribution matrix of the first word mask based on the context vector of the first word mask and a second word vector parameter matrix; and training the language model based on a word vector corresponding to the first word mask.

The disclosed subject matter relates to a system and method for providing an automated assistant that retrieves information from a knowledge base in response to a user's natural language question. A user's natural language question voice is transformed into an intermediate representation. From the intermediate representation, a cypher query is generated which may be used to query the database. The query results are provided in response to the user. The transformation into the intermediate representation is database independent while the cypher query is dependent upon the database queried.

The disclosed subject matter relates to a system and method for providing an automated assistant that retrieves information from a knowledge base in response to a user's natural language question. A user's natural language question voice is transformed into an intermediate representation. From the intermediate representation, a cypher query is generated which may be used to query the database. The query results are provided in response to the user. The transformation into the intermediate representation is database independent while the cypher query is dependent upon the database queried.

Methods, systems, and computer-readable storage media for receiving, by an aromatic simulation platform, a recipe including descriptions indicative of ingredients of a consumable, processing the recipe through a first neural network to provide a recipe embedding, processing an ingredients profile to determine an aroma compounds profile representing the ingredients of the ingredients profile, processing the aroma compounds profile through a second neural network to provide an aroma embedding, and processing the recipe embedding and the aroma embedding through a third neural network to provide an aroma profile representative of the consumable of the recipe.

Methods, systems, and computer-readable storage media for receiving, by an aromatic simulation platform, a recipe including descriptions indicative of ingredients of a consumable, processing the recipe through a first neural network to provide a recipe embedding, processing an ingredients profile to determine an aroma compounds profile representing the ingredients of the ingredients profile, processing the aroma compounds profile through a second neural network to provide an aroma embedding, and processing the recipe embedding and the aroma embedding through a third neural network to provide an aroma profile representative of the consumable of the recipe.

In a system for efficiently organizing, storing, and/or accessing project data, and for visualizing project progress, for a specified project, a fractal-based or bioinspired reference structure is selected. A file organization and storage structure is generated based on the reference structure. The reference structure includes tags that can indicate the appropriate storage locations for different types of project-related data based on the nature of the data. To storage a file, the name and/or contents of the file are analyzed and matched with one or more tags, so that the file can be stored at the location identified by the best matching tag.

In a system for efficiently organizing, storing, and/or accessing project data, and for visualizing project progress, for a specified project, a fractal-based or bioinspired reference structure is selected. A file organization and storage structure is generated based on the reference structure. The reference structure includes tags that can indicate the appropriate storage locations for different types of project-related data based on the nature of the data. To storage a file, the name and/or contents of the file are analyzed and matched with one or more tags, so that the file can be stored at the location identified by the best matching tag.

Systems and methods to implement commands based on selection sequences to a user interface are disclosed. Exemplary implementations may: store, electronic storage, a library of terms utterable by users that facilitate implementation of intended results; obtain audio information representing sounds captured by a client computing platform; detect the spoken terms uttered by the user present within the audio information; determine whether the spoken terms detected are included in the library of terms; responsive to determination that the spoken terms are not included in the library of terms, effectuate presentation of an error message via the user interface; record a selection sequence that the user performs subsequent to the presentation of the error message that causes a result; correlate the selection sequence with the spoken terms based on the selection sequence recorded subsequent to error message to generate correlation; and store the correlation to the electronic storage.