14results about How to "Meet search needs" patented technology

The invention relates to an optimization method of retrieval, in particular to an optimization method of index retrieval of a digital library, which adopts the following technical scheme: S1, a dynamic hierarchical index construction technology: firstly, performing multi-dimensional content analysis on digital resources in the library, including themes, keywords, authors and publishing time information; classifying the literatures according to the information, and constructing a content hierarchical structure; s2, an index optimization strategy based on a use mode: performing data analysis on a retrieval behavior of a user, monitoring an access frequency, a query type and an access path of the user in different types of literatures, and identifying a typical user use mode; s3, performing semantic association retrieval optimization; and S4, index updating and resource allocation optimization: when new literature resources are added into a library or existing resources are modified, updating the index in real time, and adjusting an index structure according to content classification and user behaviors.

The invention relates to the technical field of retail industry search, and particularly discloses a retail industry search system and method based on a large language model, which are characterized in that after a target commodity query statement input by a user is acquired, a natural language processing technology based on deep learning is adopted to carry out retrieval intention extension on the target commodity query statement; according to the method, more abundant query content description is generated, after the user confirms that the query content description is correct, context semantic feature extraction and fine-grained semantic query interaction are carried out on the query content description and the description information of the alternative commodities, and therefore whether the alternative commodities meet the retrieval requirement of the user or not is intelligently recognized. Through the mode, the query intention of the user can be more accurately understood, and the commodity information highly related to the query intention can be provided, so that the shopping experience and the search efficiency of the user are remarkably improved.

The invention relates to a quick form building method. The method comprises the following steps: defining a quick search custom component based on a JSON (JavaScript Object Notation) format; defining a reusable UI module based on a Vue framework, wherein the UI module receives the attribute value and triggers a custom event; the front-end component introduces a quick search custom component; defining a to-be-searched form object and transmitting the to-be-searched form object as an attribute parameter value to the quick search custom component; configuring attribute parameter values for displaying the searched data; configuring an attribute parameter value for quickly retrieving and displaying the configuration item; custom content is inserted into the rapid search custom component through a custom slot content; and using a quick search custom component in the template of the Vue component, and binding an attribute parameter value and an event monitor. According to the method, the dynamic form search is realized based on the JSON configuration, and the fields, types and verification rules of the form are defined through the unified JSON configuration file, so that the dynamic generation and management of the form interaction interface are realized.

The present invention discloses an intelligent content recommendation system, which relates to the technical field of recommendation methods, including an information capture module, a sentiment analysis module, a data processing module, a recommendation module, a login module, a detection module, an exception handling module and a display module. The information capture module crawls user data and data on the type of content to be recommended; the sentiment analysis module is used to obtain the current sentiment type of the user; the data processing module is used for data processing and uploading content keywords to a total list of content keywords. The present invention adopts a sentiment analysis module to classify user sentiment types, increases the diversity of user samples on the basis of traditional user browsing content information and historical behavior data, expands the application scope of traditional collaborative filtering algorithms, recommends content to users according to changes in user sentiment, adopts a combination of a detection module, a recommendation module and a screening module, eliminates content that users are not interested in in detail, satisfies user search needs more meticulously, and improves the accuracy of recommendation preferences for users.

The application belongs to the technical field of nuclear power business data management, aims to solve the problem of device-level integration of cross-modal data, and provides a multi-source data multi-level association retrieval method and system for DCS devices, the method receives and analyzes retrieval input, generates structured retrieval instructions, generates multi-level labels, realizes accurate matching and semantic association analysis, schedules parallel retrieval of time series databases, graph databases and full-text engines, fuses results through dynamic weight distribution and time window alignment strategy, generates a composite retrieval report, displays topological relationships in a device association graph, and presents time series curves, event markers and analysis reports in a multi-modal view, and realizes penetrating analysis from process chain to device parameters through real-time updating of content; the system comprises a retrieval service layer, an association model layer and a data source layer. The application realizes multi-level data penetrating retrieval from the device physical layer to the process logic layer and then to the event context layer, and provides full-link data tracing capability for industrial scenes.

The invention belongs to the technical field of document retrieval, and particularly relates to a multi-modal long document retrieval method based on hierarchical representation and double-branch retrieval. According to the method, three-level hierarchical document representation composed of an element level, a page level and a chapter and section level is constructed by designing hierarchical features oriented to a document structure; a double-branch retrieval mechanism is used for conducting semantic-level matching and feature-level matching on queries, and a final evidence set is generated through a fusion strategy. According to the method, the cross-page semantic association and the fine-grained visual clues can be utilized at the same time, effective retrieval and information positioning of the multi-modal long document are achieved, the retrieval requirements of documents with different layout forms and different lengths in a real scene are met, and the method has important practical application value.

The invention discloses an internet-based trade data search method and search system, and relates to the technical field of data search, and the method comprises the following steps: obtaining cross-border trade characteristics by using a cross-border analysis method; performing character extraction on the search trade data to obtain search data features, and performing search feedback to the user based on the preliminary judgment; searching the search trade data based on the search feedback, and sending a search result to the user; the method is used for solving the problems that in an existing trade data search method, when the search name of a user is wide, a search platform can provide a large number of search results with weak relevance for the user, so that the search efficiency of the user is reduced, the user cannot be assisted to improve the search name, and the search requirement of the user cannot be met.

The invention discloses a retrieval method, device and equipment based on a knowledge graph and a medium, and relates to the technical field of retrieval, the method comprises the following steps: obtaining a target retrieval word input by a user, a historical retrieval word and a historical retrieval entity corresponding to the historical retrieval word; querying a first retrieval entity matched with the target retrieval word in the knowledge graph; determining a second retrieval entity matched with the target retrieval word from the historical retrieval entities according to the target retrieval word, the historical retrieval words, the historical retrieval entities and the first retrieval entity; determining a historical search word corresponding to the second search entity as an intention search word of the user; and determining the first retrieval entity, the second retrieval entity and the intention retrieval word as a target retrieval result of the target retrieval word. According to the method, the retrieval results of the retrieval words are enriched, and the retrieval requirements of users can be met.

The application provides a time series data hybrid retrieval method, device and equipment for a security scene. The method comprises: data storage by using a multi-database cooperative storage architecture, the multi-database cooperative storage architecture comprising a vector database, a structured database, a cache database and a raw data backup database, each database storing corresponding type data according to a preset rule; according to a retrieval request of a user, retrieving results are obtained from the structured database, or a hybrid retrieval mode is started to obtain retrieval results from the vector database and / or the structured database; and the retrieval results are returned to the user. It can be seen that the application realizes efficient hybrid retrieval of structured attributes and high-dimensional feature vectors, improves the time series data retrieval performance and storage efficiency, and meets the large-scale and high real-time retrieval requirements of the security scene.

The invention discloses a method and a device for identifying a search intention of an automobile part, and relates to the technical field of computers. A specific embodiment of the method comprises the steps of performing entity recognition on an input automobile part search text to obtain a vehicle model entity, a part type entity and a specification parameter entity; semantic fusion is carried out on the vehicle type entity, the accessory type entity and the specification parameter entity and an adaptation rule in a knowledge graph, a fusion feature vector is generated, and the adaptation rule formed by the adaptation relation among the vehicle type, the accessory type and the specification parameter is stored in the knowledge graph; weighting the fusion feature vector based on the adaptation rule weight matrix; and processing the weighted fusion feature vector by adopting an intention recognition model based on an attention mechanism to obtain an intention recognition result. According to the embodiment, the recognition accuracy of the search intention is improved, and cross-vehicle-type fitting and rapid fitting of novel fittings can be realized.

The embodiment of the invention discloses a search component display method and device.According to the main technical scheme, the method comprises the steps that a playing page used for playing media files is displayed, a first search component is displayed on the playing page, and the first search component is used for skipping to a first search page after being triggered by a first operation gesture; the first search page is used for executing a search task; in response to the operation of triggering the component switching function, a second search component is displayed on the playing page, and the visual layout attribute of the second search component is obtained based on the behavior information of the user within the preset time and / or the basic information of the user. In this way, the visual effect is improved, the user can conveniently and rapidly search, and then the search experience of the user is improved.

The invention relates to the technical field of computers, and discloses a data search method and device, equipment, a medium and a product. The method comprises the following steps: acquiring current search data and reference data corresponding to the current search data; determining a target search demand corresponding to the current search data based on the search demand corresponding to the reference data; and displaying a search result corresponding to the target search demand on a search result page. By implementing the technical scheme of the invention, accurate pre-judgment of the search demand of the user can be realized, so that the search result meeting the search demand of the user can be accurately obtained, and the user experience is improved.

This invention relates to the field of information retrieval and data visualization technology, and discloses a visual text search method based on a hybrid data model. The method includes: constructing a hypergraph hybrid model by associating a graph database and a vector database using global identifiers; identifying the intent of user queries; generating structured search instructions for the graph database and semantic similarity search instructions for the vector database; fusing and expanding the two types of search results based on global identifiers to form a search result set containing an extended knowledge graph, a list of semantic vectors, and traceable links between them; and finally, converting the result set into a dynamic and interactive visual view according to predefined mapping rules and a hybrid mechanics layout algorithm. This invention effectively unifies semantic retrieval and relational retrieval, improves the comprehensiveness and accuracy of retrieval, and significantly enhances the depth of information understanding and user experience through intelligent visualization and interaction mechanisms.

The present application discloses a training method, device, medium and equipment for a search result classification model, which relates to the field of artificial intelligence. The method includes: obtaining a training data set, the training data set includes search query terms and search results corresponding to the search query terms; determining the similarity between the search query terms and the search results based on a target text matching algorithm; determining a classification label for a sample based on a preset classification interval and the similarity, the sample including the search query terms and the search results; fine-tuning the pre-trained language model based on the sample and the corresponding classification label to obtain a search result classification model. The search result classification model obtained based on the method provided by the present application can make the obtained search results more matched with the search query terms in the similarity dimension, improve the search speed, and meet the user's search needs.