135 results about "Search intent" patented technology

The invention discloses a search method and system based on computer natural language processing, and the method comprises the steps: extracting a synonym set and a context association relationship of keywords in a query text through a preset semantic knowledge graph, and generating a semantic vector representing a semantic dimension in combination with a deep learning model; extracting a historical behavior feature sequence from the query log based on the semantic vector, and analyzing a user search intention by adopting an attention mechanism model; performing similarity matching on the pre-constructed database by utilizing a semantic matching algorithm, and screening an information matching set meeting a threshold value; performing distributed processing on the matching set through a context-aware dynamic fragmentation algorithm, and constructing an index fragmentation cluster; semantic aggregation is realized by adopting a cross-fragment graph attention network, and an optimized search result set is generated through dynamic semantic projection. According to the method, through multi-modal fusion of the semantic knowledge graph and deep learning and in combination with a dynamic distributed processing architecture, the accuracy of search intention recognition and the efficiency of large-scale semantic matching are improved.

The present application relates to a method for searching for a building information model. The method comprises: performing multi-modal feature extraction on building information models in a model library to be searched, and obtaining multi-modal features corresponding to various building information models, the multi-modal features comprising semantic features, topological features, and geometric features; acquiring a search text inputted by a user, parsing the search text, and obtaining search intention information corresponding to the search text, the search intention information comprising search intention semantic features, search intention topological features, and search intention geometric features; on the basis of deep embedding learning, calculating comprehensive similarities between the search intention information and the multi-modal features of the building information models in said model library; and, on the basis of a sorting result of the comprehensive similarities between the search intention information and the multi-modal features of the building information models in said model library, determining a building information model that serves as a search result corresponding to the search text, and recommending the search result to the user.

The invention discloses a lightweight display interface rendering optimization system, which relates to the technical field of image processing, and comprises an acquisition module, an interface analysis module, a behavior analysis module and an attention analysis and rendering module, dynamically calculating an effective view radius by utilizing a visual tunneling effect; the interface analysis module performs character string fuzzy matching in combination with the context input by the user, identifies the search intention of the user and improves the weight of a corresponding component; the attention analysis module performs multi-modal weighted fusion on the physiological fixation data and the sparse content saliency thermodynamic diagram; according to the method, by recognizing the semantic intention and the physiological fixation point of the user, on the premise that core visual experience continuity is guaranteed, GPU load and video memory bandwidth occupation are remarkably reduced, and balance of high-performance display and low-power-consumption operation is achieved.

The invention discloses a search intention recognition method and device, equipment and a storage medium, and relates to the technical field of reinforcement learning, and the method comprises the following steps: generating training data based on an original corpus; performing supervision fine tuning processing on the lightweight language model based on the training data to obtain a fine tuning trained lightweight language model; performing strategy optimization on the lightweight language model subjected to fine tuning training through an improved GRPO reinforcement learning algorithm to obtain a lightweight language model subjected to reinforcement training; constructing a double-model hybrid architecture based on a short thinking chain model and a thinking chain-free model in the lightweight language model subjected to enhanced training; and outputting a final sequence of the related documents of the search terms of the user through the double-model hybrid architecture. According to the technical scheme of lightweight language model fine tuning, reinforcement learning optimization and double-model hybrid reasoning, the target search scene recognition accuracy is improved, the real-time response speed is high, and training time consumption and reasoning resource requirements are reduced.

The invention provides a medical knowledge base semantic search method and system, a medium and equipment. The method comprises the steps of obtaining a natural language query text input by a user; identifying the natural language query text to obtain key information; mapping the key information to corresponding entity nodes and relationships thereof in a knowledge graph to obtain a mapping result; the knowledge graph is constructed based on medical knowledge; and sorting the mapping results, and obtaining a search result according to the sorting. According to the method, the key information in the text is obtained by recognizing the natural language query text input by the user, so that compared with an existing search engine, the natural language query text of the user is analyzed more thoroughly, and the search intention of the user can be understood more deeply. Furthermore, according to the application, the mapping results are sorted, and the mapping results with low association degree with the search intention of the user are excluded, so that the accuracy of the search results is improved.

Provided in the present disclosure are a commodity object search method and apparatus, and an electronic device and a storage medium. According to the embodiments of the present disclosure, on the basis of a search request triggered on the basis of a client, search basis data for searching for a commodity object may be acquired first; then, on the basis of the search basis data, a first prompt word corresponding to a commodity object search scenario is generated, and interaction with a large language model is performed by means of the first prompt word, so as to obtain search intent information corresponding to the current commodity object search; and finally, on the basis of the search basis data and the search intent information, a second prompt word corresponding to the commodity object search scenario is generated, and interaction with the large language model is performed by means of the second prompt word, so as to obtain a search result corresponding to the current commodity object search. By using the solution, interaction can be performed with a large language model, so as to deeply analyze and understand a search intent of a client user in searching for a commodity object, and provide a more accurate commodity object recommendation scheme on the basis of the search intent.

The present invention discloses a knowledge graph application method based on big data, and the method comprises the following steps: step one: identifying the target entity and the search intention that the user wants to find from the query submitted by the user; step two: matching the trigger word of the set target entity with the abstract trigger word of the event class, extracting personalized features based on the matched target entity, and predicting the user's preference; step three: each vertical field performs multi-angle recommendation in this field based on the knowledge graph architecture; step four: establishing application rules for multiple vertical fields, applying the knowledge graph of the target entity obtained from the query and the matched event class project to multiple vertical fields, and the user generates a user's interest prediction value for event project recommendation based on the user feature vector extracted from the knowledge graph and the event project feature vector. The present invention has the characteristics of accurate matching and strong correlation recommendation.

Provided is an image-based search processing method, an electronic device and a storage medium, relating to the technical fields of computer vision, deep learning, natural language processing, and searching. The method includes: determining, in response to receiving an image sent by a terminal, a first requirement corresponding to the image, the first requirement including an original search intent of a user; generating a search result and a recommended content corresponding to the image according to the first requirement in a case where the first requirement meets a recommendation triggering condition; and returning the search result and the recommended content to the terminal to cause the terminal to output the search result and the recommended content on a search result page.

According to embodiments of the disclosure, a method, an apparatus, a device and a medium for book search are provided. The method includes: acquiring query information of a user; determining a book search intent of the user at least based on the query information; determining at least one book matching the book search intent; determining recommendation information for recommending the at least one book to the user at least based on the book search intent; and providing a response to the query information to the user, the response including an indication of the at least one book and the recommendation information. Thereby, it is possible to quickly and accurately meet a user's personalized book search needs, and providing the recommendation information that better matches the intent can improve user satisfaction and conversion rate of book recommendation.

The invention discloses a legal service intelligent searching and pushing system based on user requirements, particularly relates to the field of information processing, and is used for solving the problems of missing evidence binding and insufficient version anchoring in existing retrieval and touch. Executing structured positioning according to the retrieval intention to generate a fragment anchor identifier, querying a leatherwise table by the fragment anchor identifier to complete version coincidence judgment and paraphrasing closing judgment to generate an effective fragment pointing and rebounding entry, reading a touch node to bind and generate touch content, embedding the touch content into the rebounding entry, recovering a rebounding drop point, checking consistency and correcting a record, and performing rebounding. And a closed evidence chain of retrieval, judgment, reaching and checking is realized.

The invention provides a photo album image searching method and device, equipment and a storage medium, and the method comprises the steps: obtaining description information related to a to-be-searched image, transmitting the description information to a semantic recognition model server, receiving a first image tag from the semantic recognition model server, and transmitting the first image tag to a server; a target image label matched with the first image label is determined from second image labels corresponding to each image in the photo album, the second image labels are obtained by recognizing each image through a preset target recognition model, a to-be-searched image is determined based on the target image labels, and the to-be-searched image is searched according to the to-be-searched image. The image recognition model can be deployed on the end side to recognize the tag of the image, the semantic recognition model server is called to recognize the search intention to obtain the corresponding tag, and the to-be-searched image is further obtained through tag matching, so that model miniaturization processing does not need to be performed on the end side to reduce the model performance; therefore, the image searching effect in the photo album is improved.

The invention discloses a search intention recognition method based on an NL2SQL model, relates to the technical field of data retrieval, and solves the problems that in the prior art, SQL query writing in the data analysis process needs a large amount of manual participation, time is consumed, and the requirements for the technical level and experience of operators are high. According to the method, the original data is converted into the data items by constructing the business knowledge base and the business dictionary base, and the SQL statements are constructed based on the data items. The method has the advantages that natural language query can be understood and converted, so that non-technical users can easily perform database query. Natural language query is converted into SQL statements by training a pre-training language model, so that the threshold of using a database by a user is greatly reduced. According to the method, the retrieval accuracy is improved, the user experience is enhanced, and database query becomes more visual and convenient. The method brings innovation and progress to the field of information retrieval.

The embodiment of the invention relates to the field of large models, and provides a method and device for searching commodities based on a multi-modal large model and a program product, and the scheme comprises the steps: carrying out the data enhancement of user input based on a query generation model, and determining a first commodity search intention according to a target commodity key feature set obtained through the data enhancement; inputting the first commodity search intention into a generative model to obtain multiple groups of images and commodity description information of candidate pairs of feature tags matched with the images; responding to a second input of the user to the target candidate pair; traversing the e-commerce transaction platform to obtain a target commodity, wherein the matching degree of the first commodity search intention of the target commodity is higher than a first threshold value; and displaying the target commodity according to the matching degree of the target commodity and the first commodity search intention. According to the scheme, on the basis of accurately recognizing the commodity search intention of the user, the user does not need to change input for multiple times and manually confirm whether the recommended commodity meets the own demand for multiple times, and the commodity search efficiency and search accuracy are remarkably improved.

The invention discloses a search method, system and device, a program product and a storage medium. The method comprises the steps of obtaining a search statement; analyzing the search statement based on an intention recognition model to obtain a search intention; based on the search statement, a retrieval mode suitable for the search statement is selected, and the intention recognition model is used for recognizing the intention and demand of an initiator of the search statement according to the search statement; determining preparation information corresponding to the search statement based on the retrieval mode and the search intention; on the basis of at least one of a personalized model, a sorting model and a deep learning model, a search result corresponding to the search statement is generated, and the personalized model is used for screening the preparation information according to the social network relation of an initiator of the search statement and / or preference information. Therefore, the search result better meets the personalized requirements and behavior modes of the user, and the user experience is remarkably improved.

A user interface of an online system is generated based on search for relevant items that match ingredients of a recipe. After receiving, from a device associated with a user of the online system, a query for an ingredient of a recipe, the online system identifies, based on one or more attributes in the query, a set of candidate items for the ingredient. The online system generates a recipe relevance score for each candidate item by applying a weighted sum of scores, ranks the identified candidate items based on their recipe relevance scores, and selects one or more items for presentation to the user. The online system then generates a user interface of the device with a recipe page including the ingredient of the recipe and the one or more items that match the ingredient of the recipe.

The invention discloses a personalized search method and system for an electric power knowledge base, and relates to the technical field of electric power informatization and intelligent search, and the method comprises the steps: generating a user interest vector representing the current search intention of a user through a weight adaptive algorithm, and constructing a user interest model for the electric power field; receiving a query request input by a user, and retrieving from the power knowledge base based on the query request to obtain a corresponding initial search result set; constructing a queried power field polysemy model based on formal concept analysis (FCA); calculating the similarity between the interest vector and each semantic category based on the user interest vector; reordering the documents in the initial search result set according to the similarity; and selecting a feature word from the semantic category with the highest similarity as an expansion word. According to the method, through user interest modeling and semantic category matching, accurate sorting of the power knowledge base results is achieved, the retrieval individuation degree is improved, and the search accuracy and the user experience are improved.

The embodiment of the invention discloses a search method and electronic equipment, in the method, the electronic equipment can identify the search intention of a user, implement priority search based on the search intention of the user, and preferentially present a target search result meeting the search intention of the user, so that the waiting time of the user for obtaining the target search result can be obviously shortened, and the user experience is improved. The user can conveniently notice the target search result at a glance, and the attention burden of the user is relieved. Moreover, the search triggering and the search intention transmission can be combined into one on the user operation, and the user does not need to separately implement the user operation for triggering the search and the user operation for transmitting the search intention, so that the user operation is simplified, and the machine using efficiency is improved.

The invention discloses a retrieval result display method and system, and relates to the technical field of data processing.The method comprises the steps that a retrieval result tree containing hierarchical nodes is constructed and displayed on a superficial layer of a terminal interface, and an expandable mark is set; collecting user browsing behaviors through sight tracking, and calculating attention popularity; recognizing a retrieval intention in combination with the popularity, the result tree and the user portrait; and generating a deep display instruction according to the retrieval intention, controlling an interface to display a deeper result, and realizing personalized information presentation. Therefore, the technical effects of accurate intention recognition, active information pushing and personalized and efficient retrieval result display are achieved.

The invention provides a man-machine interaction method and device, equipment and a storage medium, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining multi-modal data of a current interaction round, the multi-modal data at least comprising an input image and an input text; based on the input image, performing image recognition by applying a multi-modal large language model to obtain image information corresponding to the input image; based on the input text, performing intention recognition by applying a multi-modal large language model to obtain a retrieval intention corresponding to the input text; based on the image information, the retrieval intention and a historical commodity retrieval result corresponding to the historical interaction round, performing decision analysis by applying a multi-modal large language model, and determining a retrieval strategy; the retrieval strategy comprises a joint knowledge base retrieval strategy, a historical retrieval result reuse strategy or a non-retrieval strategy; and obtaining reply information based on the retrieval strategy. Differentiated retrieval is performed according to actual retrieval requirements, so that consumption of invalid resources is reduced, and retrieval efficiency is improved.

The invention discloses an information search method and system, electronic equipment and a storage medium. The method comprises the steps of obtaining current context information, a current search text, a current figure image and a historical search result sequence of a user; analyzing the current context information based on a context sensing mechanism to obtain a current analysis search intention of the user; fusing features of the current search text and features of the current figure image into multi-modal data in a pre-trained convolutional neural network of the current search text and the current figure image, and analyzing current emotion information of the user by using the multi-modal data; inputting the historical search result sequence into a pre-trained prediction model, and predicting to obtain a current predicted search intention of the user; according to the current analysis search intention, the current emotion information and the current prediction search intention of the user, current search results searched based on the current search text are adjusted and sorted, and a final search result is obtained and output.

To provide a data processing device, method, and program for appropriately responding to user inputs.SOLUTION: In a data processing system 10, a data processing device is configured to: input, upon receiving a creation sentence as input data, a prompt including a problem solvable by its content and an indication for creating a summary of the creation sentence, as a first prompt, to a data generation model; acquire the result of first specific processing; input, when the input data is a search query, a prompt including the query and an indication for querying the intent of search of a browsing user assumed therefrom, as a second prompt, to the data generation model; acquire the result of second specific processing; input a prompt including an indication for querying a list of summaries associated with the problem corresponding to the intent of search corresponding to the second prompt, as a third prompt, to the data generation model; acquire the result of third specific processing; and output the result of third specific processing and the creation sentence when having acquired interest information.SELECTED DRAWING: Figure 1

The invention provides a natural language-based search method and system, and the method comprises the steps: obtaining an input natural language demand, and obtaining an input demand; an intention recognition agent is adopted to conduct intention analysis on the input requirement to obtain a search intention, the intention recognition agent is an agent obtained through pre-training and used for understanding a natural language, and the search intention is a target expected to be achieved by the target object; and performing retrieval according to the search intention to obtain retrieval data, and sending the retrieval data to target equipment used by the target object, so that the target object processes the business by using the retrieval data. According to the method, the problem that in the prior art, a bank APP search function mainly depends on a keyword matching technology, and the search accuracy is low is solved.

The data retrieval method comprises the following steps: performing OCR (Optical Character Recognition) and paragraph splitting on an original document to generate a parent segmentation abstract and a child segmentation abstract which have a hierarchical relationship, and fusing an abstract text with metadata to obtain an abstract file; constructing a structured data abstract directory containing semantic features and attribute features; obtaining user dialogue history and current input, constructing a semantic input matrix, and performing semantic analysis and intention reasoning under role and task constraints by using a large model to generate a standardized search intention; inputting the standardized search intention and the structured data abstract directory into a large model, screening candidate abstracts through a bidirectional association matching mechanism, performing hierarchical mapping based on a knowledge base index rule, and reasoning to generate an original storage index of target data; and carrying out validity verification on the original storage index generated by reasoning, obtaining original data content according to the index passing the verification, and returning the original data content.

The embodiment of the invention discloses a live broadcast interaction method and device, equipment, a storage medium and a program product. The method comprises the steps of displaying a search result page in response to a search operation based on target search information; at least one e-commerce live broadcast included in the search result page is a live broadcast of a live broadcast commodity including a target commodity in the live broadcast shopping cart, and the target commodity is determined according to the target search information; in response to a selection operation on a target e-commerce live broadcast in the at least one e-commerce live broadcast, determining a target commodity matched with the target search information in a live broadcast shopping cart of the target e-commerce live broadcast, displaying a live broadcast interface of the target e-commerce live broadcast, and displaying a commodity card in the live broadcast interface of the target e-commerce live broadcast, the commodity card is used for trading the determined target commodity. By adopting the embodiment of the invention, the search intention of the user can be accurately identified, so that the user can realize seamless switching between search and live broadcast transaction, and thus the live broadcast interaction efficiency is improved.

Alternative options are presented to users at the point of personalization of a search engine to generate personalized query suggestions. Seed items within a module carousel comprising item cards on a homepage are identified. Embeddings are retrieved for at least a portion of the seed items. Based on the embeddings, related item embeddings corresponding to related items that were purchased by other users are identified. A list of queries for each of the related items that were purchased by the other users is retrieved. A ranking for each query of the list of queries is generated. Based on the ranking, queries of the list of queries are presented in place of at least one of the item cards within the module carousel. In various aspects, the queries of the list of queries broaden the intent, narrow the intent, or diversify the intent.

The invention provides a search processing method and device, electronic equipment, a storage medium and a program product, and relates to the technical field of data processing.The method comprises the steps that it is detected that operation of a user focuses on a search box, and the search intention of the user is determined; determining a search guide word according to the search intention; and if a confirmation instruction of the user for the search guide word is received, determining a search result according to the search guide word. In the embodiment, the search guide word is determined according to the search intention, and then the search result is determined according to the search guide word, so that the problem that the search result is inaccurate due to the inaccurate search word can be avoided, the search guide word is determined according to the search intention of the user, and the search result obtained according to the search guide word is more accurate; a user can be helped to quickly search a wanted result, and the search accuracy is improved.

This invention belongs to the field of computer information processing and proposes a document retrieval optimization method based on entity association. It performs secondary optimization while retaining the original retrieval algorithm, which not only improves the accuracy of the retrieval but also avoids the accuracy and efficiency problems caused by algorithm modifications. By performing entity recognition on both the document set and the user's search content, and calculating the association relationships between entities and documents, and entities and search content respectively, and comprehensively applying these association coefficients, it can uncover deep semantic relationships between search content and documents, and accurately locate documents that match the search intent. By calculating entity association degrees and re-ranking them according to these degrees, the accuracy of the search results is improved, resulting in a higher degree of alignment with user needs and allowing users to more easily obtain the information they require.

The invention provides a search method and system, a product application and a storage medium. The search method comprises the following steps: performing intention recognition on a user search dialogue to obtain a search intention; based on the search intention, determining a knowledge base associated with directional query of the search intention as a target knowledge base; and searching the search intention from the target knowledge base to obtain an intention result, and outputting the intention result. Therefore, the search intention is used, the associated knowledge base is directionally queried, learning is fast, the whole knowledge base does not need to be queried, query efficiency is high, and the effect is good. In addition, learning training or keyword configuration in advance is not needed, and the cost of repeated practice is reduced. Meanwhile, through the search intention, complex user search dialogues can be achieved, the query capacity is high, and the search result better meets the user expectation.

The invention discloses an intelligent archive retrieval method and system based on a large model, and relates to the technical field of archive management, and the specific steps are as follows: collecting archive data, analyzing unstructured archive data, structuring the archive data, preprocessing the archive data, and removing redundancy in the data; converting the cleaned archive data into a digital form, inputting the digital form into a large model for training, establishing a local large model, performing fine tuning on model training by adopting a supervised fine tuning method, finally automatically capturing key information and retrieval intention of real-time retrieval, and searching archive resources highly matched with the key information and retrieval intention in an archive database through the large model. Archive text abstracts, knowledge retrieval answers, knowledge maps, archive knowledge recommendation and the like are generated and visually displayed through a user terminal. According to the method, the problem of unstructured archive processing is solved, and multi-dimensional archive knowledge output and visualization are completed by establishing a deep semantic understanding system driven by a local large model.