A service node receives a document creation request sent by a first user for creating a digital document of title of a target asset. The document creation request includes first configuration information of a digital document of title to be created. The first configuration information is generated by the first user by performing a configuration operation on each component in a corresponding first document template based on related information of the target asset. The first document template is a template that matches the related information of the target asset in a plurality of document templates corresponding to a first blockchain. A digital document of title is generated based on the first configuration information and a predetermined document generation rule, and stored in the first blockchain, so the target asset is circulated by using the first blockchain based on the digital document of title.

A system for selecting different aspects of data objects to be matched with similar aspects of other data objects. A user inputs a search data object and a value. A neural network computes features for the search object at multiple layers that correspond to different aspects of the object. A descriptor is generated for the search object from features output at a layer position of the neural network determined from the value. The descriptor is compared to corresponding descriptors for objects in a collection to select objects that include aspects similar to an aspect of the search object. The user can change the value to view different objects that include aspects similar to other aspects of the search object. Thus, the user can explore different aspects of an object to find objects that include aspects similar to the aspect of the object that the user is interested in.

Systems and methods for responding to a natural language query are disclosed herein. A query for an entity associated with a plurality of content types is received via a user interface of a computing device. A determination is made as to whether the query specifies any one or more of the plurality of content types. In response to determining that the query specifies one or more of the plurality of content types, a response to the query is generated for visible or audible presentation via the computing device, with the response comprising results from the one or more specified content types. In response to determining that the query lacks specification of any one or more of the plurality of content types, a response to the query is generated for visible or audible presentation via the computing device, with the response comprising results from each of the plurality of content types.

Disclosed are methods, systems, and non-transitory computer-readable medium for filtering vehicle information. For instance, the method may include receiving a vehicle search request from a user device, the vehicle search request including conditions with corresponding weights. The method may also include, in response to receiving the vehicle search request, forming a search query based on the conditions and the weights of the vehicle search request; obtaining vehicle information; filtering the vehicle information based on the search query to obtain a result set and a partial match set; and transmitting a search result message based on the result set and the partial match set to the user device.

Methods, systems, and computer-readable media provide a real-time Q&A interface, such as an online chatbot, either standing alone or as a live agent assistant, with predicative Q&A and resource suggestions. In one embodiment, the real-time Q&A interface uses data extracted from a user inquiry to identify and display a primary response, identify suggested inquiries from a knowledgebase and provide a user-selectable suggested inquiries indicator, and identify suggested content items from related content libraries or webpages and provide user-selectable suggested content item indicators. In one embodiment, the suggested content items include related videos and links to webpages with related content.

A visual-programming tool processes nodes of a graph corresponding to operations or functions in program code associated with a plurality of programs, (e.g., games), stored as graph of nodes with logical connections signifying inputs, outputs, and/or units of connected nodes. The visual-programming tool resolves valid types and/or units associated with respective connected nodes and can propagate valid types and/or units throughout the graph.

Methods and apparatus to facilitate generation of database queries are disclosed. An example apparatus includes a generator to generate a global importance tensor. The global importance tensor based on a knowledge graph representative of information stored in a database. The knowledge graph includes objects and connections between the objects. The global importance tensor includes importance values for different types of the connections between the objects. The example apparatus further includes an importance adaptation analyzer to generate a session importance tensor based on the global importance tensor and a user query, and a user interface to provide a suggested query to a user based on the session importance tensor.

Systems and methods are disclosed for recommending query parameters to a user based on tenant information. The system can identify a token query parameter from a portion of a query entered in a user interface. The token query parameter can correspond to a system query parameter, such as a query command, a function, etc., or to a user query parameter. The system can identify a tenant of a distributed data intake and query system that is associated with the query. Based on the token query parameter, the system can identify at least one query parameter associated with the tenant. The at least one query parameter can include one or more query parameters previously entered by the user or other users of the tenant, etc. The system can cause the user interface to display one or more recommended query parameters for inclusion in the query.

Expanding search engine functionality using AI models. A method includes, as part of a search session, receiving user input at a search engine. One or more searches on a set of data using the user input. Search results are provided from the one or more searches to a user. Based on a history of the search session, suggestions are provided in a user interface of AI models that could be applied to expand potential search results for the search session. User input is received at the user interface selecting one or more of the suggested AI model. The one or more selected AI models are applied to expand the set of data. Search results to the user based on searching the expanded set of data.

Embodiments of the present disclosure relate to an article processing method, electronic device, and computer program product. The method includes: determining, based on content of a target article, a target article vector associated with the target article; acquiring a reference article vector set associated with a reference article set; and determining, based on a distance in an article vector space between the target article vector and a reference article vector in the reference article vector set, a reference article vector associated with the target article vector in the reference article vector set as an association article vector. By using the technical solution of the present disclosure, an association article associated with a target article can be accurately provided based on the target article selected by a user, so that reports on the target article and its association articles can be further provided to the user for analysis and selection.