98 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 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.

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.

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.

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 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.

The application discloses a search result reordering method and device, equipment and a computer storage medium, and relates to the technical field of media content search. In the method, a suitable timing is intelligently selected to trigger a reordering process according to real-time interaction between a target object and media content during a search session, the un-consumed media content in a search result list of the search session is reordered, and the reordered search result list is presented to the target object. The method adjusts the order of each media content in the search result according to instant interest, can improve the accuracy of the result presentation of the search session, improves the content searching efficiency, and solves the problem that the interaction behavior feedback of the target object is not timely in the media content search scene. The order of the search result is adjusted in time to meet the search intention of the user.

The invention relates to a site information search method and device, a vehicle, a storage medium and a program product, and relates to the technical field of search, and the method comprises the steps: responding to a search request of a user for a target site, and outputting an information search result corresponding to the target site to the user, the information search result is obtained based on the current vehicle state data and the search request data. According to the method, the information search result more conforming to the current search scene can be searched according to the vehicle state data and the search request data, so that the information search result more meets the search intention of the user, personalized search is realized, and the search experience of the user is improved.

The embodiments of the present application disclose a live broadcast interaction method, apparatus, device, storage medium, and program product. The method includes: in response to a search operation based on target search information, displaying a search result page; the search result page includes at least one e-commerce live broadcast, the target product is determined based on the target search information; at least one e-commerce live broadcast is determined based on the target product, and at least one e-commerce live broadcast is a live broadcast of live products including the target product; in response to a selection operation of a target e-commerce live broadcast in at least one e-commerce live broadcast, displaying the live broadcast interface of the selected target e-commerce live broadcast. The embodiment of the present application can accurately identify the user's search intent, allowing the user to seamlessly switch between search and live transaction, thereby improving the efficiency of live broadcast interaction.

This application provides a method, electronic device, and storage medium for identifying boiler weld defects. The method includes: acquiring a radiographic digital image of a sample to be evaluated and corresponding metadata; obtaining a first parameter set based on a preset defect detection model; obtaining a second parameter set and search intent for each suspected defect based on the first parameter set and metadata, using a pre-trained large language model; inputting the search intent into an industry standard database and a historical case database to obtain standard evidence and historical case evidence; determining an initial defect based on the first parameter set, the second parameter set, the standard evidence, and the historical case evidence; obtaining a consistency score by combining the first parameter set, the second parameter set, the standard evidence, and the historical case evidence; and correcting the initial defect using the consistency score to obtain the boiler weld defect identification result. This application improves the accuracy and reliability of defect identification results.

The invention discloses a file searching method, device and equipment, a medium and a product, and belongs to the technical field of electronic equipment. The file search method comprises the steps that in response to a search intention of a user, a first interface is displayed, the first interface comprises metadata, the metadata comprises a virtual file handle and a file name of a candidate file, and the candidate file is associated with the search intention; receiving a first input to target metadata, wherein the target metadata is at least one of the metadata; and in response to the first input, displaying the file content of the target file corresponding to the target metadata.

The invention relates to the technical field of intelligent search, and discloses an intelligent agent-based e-commerce product search method and device, a medium and a program product, the method comprises the following steps: receiving a current round of search input of a user, and analyzing and constructing a search condition; comparing historical search conditions, collecting change characteristics, and judging the stable state of the search intention; calling a search engine to output a commodity result, collecting user interaction behaviors, and judging a trust state of a search result; and adjusting a subsequent search condition construction strategy and / or a commodity sorting strategy according to the combination linkage of the two, and finally outputting a commodity search result. According to the method, the stability of the search intention and the credibility of the result are jointly evaluated and dynamically adjusted, negative circulation formed by the stability and the credibility of the search intention is broken, repeated search and invalid recommendation are reduced, the matching accuracy of the search result and the credibility of the user are improved, and e-commerce search experience and conversion efficiency are optimized.

A computing system obtains text that relates to an experience of a user and determines a search intent based upon the text and a context of the user, where the context is determined based upon activity history of the user in a plurality of applications. The computing system identifies potential keywords in the text and identifies a search domain in a plurality of search domains based upon the potential keywords. The computing system computes a confidence score for each of the potential keywords based upon the search domain, the context, and prior search queries of the user. The computing system identifies keywords from amongst the potential keywords based upon the confidence scores and executes a search over an index based upon the keywords, where the index indexes user content of the user and content of an enterprise. The computing system presents search results for the search to the user.

The invention provides an information retrieval method and system based on large model deep search and real-time semantic analysis, and relates to the technical field of information retrieval and artificial intelligence. The method comprises the steps that according to a domain semantic association database, a local multi-level association keyword library is constructed and dynamically maintained; receiving a user search word, performing intention analysis on the user search word through the large model to generate user search intention information, and performing initial retrieval according to the user search intention information to generate initial retrieval result information; performing real-time semantic verification on the preliminary retrieval result information, and screening out target preliminary retrieval result information or no matching result identifier; if no matching result identification is generated, matching the user search word with a local multi-level associated keyword library, and screening out a high-association-degree expansion word; executing secondary retrieval to generate target secondary retrieval result information; and combining and sorting the target secondary retrieval result information and the target preliminary retrieval result information, and then outputting.

This application discloses a search method and related apparatus. The processing device can first identify the text type corresponding to the search text, and then use different category intent recognition methods for different text types to determine the category corresponding to the search text. Finally, based on the category, it returns the target object corresponding to the search text. Therefore, on the one hand, the category intent recognition method can better match the text features, resulting in more accurate category recognition results; on the other hand, it can overcome the limitations of text relevance, obtaining more comprehensive search results, and ultimately providing users with target objects that better match their actual search intent. This is particularly beneficial in e-commerce scenarios where the text relevance between object information and search text is often poor, significantly improving the user's search experience. This application relates to artificial intelligence technology and can be applied to related scenarios of in-vehicle IoT.

The invention discloses a program channel fuzzy search method and device based on a large model, a terminal and a medium, and belongs to the technical field of information retrieval and intelligent interaction.The program channel fuzzy search method comprises the steps that channel lists and program lists provided by program service providers are collected and obtained regularly, and a knowledge base oriented to the large language model is constructed; acquiring a search request initiated by a client, and performing intention recognition and semantic analysis on the search request to recognize a search intention of a user; based on the recognized user search intention, semantic retrieval is executed, channels or program items matched with the expression content of the search intention are searched, and a search result list in the form of a sorting list is generated; receiving an operation instruction of a user, and selecting and determining a program channel from the search result list; and performing corresponding playing control based on the selected determined program channel. According to the method, the accuracy and interaction experience of the user in the content retrieval process can be obviously improved.