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Welding process parameter recommendation method for enhancing large model by using knowledge graph retrieval
InactiveCN119578525Aefficient managementRealize intelligent recommendationInference methodsManufacturing computing systemsKnowledge graphData mining
According to the welding process parameter recommendation method using the knowledge graph to retrieve the enhanced large model, the welding process knowledge graph is constructed, multi-source heterogeneous welding knowledge is stored in the graph, and effective management and reuse of the welding knowledge are achieved; meanwhile, through user feedback and verification, the welding process knowledge graph can be continuously updated and perfected, and continuous accumulation and iterative optimization of knowledge are achieved; the welding process knowledge graph is used as an external knowledge base to retrieve and enhance the large model, and accurate and comprehensive welding process related knowledge can be provided for the large model to serve as a reasoning basis, so that the illusion problem of the large model is effectively relieved; according to the method, intelligent recommendation of the welding process parameters is realized, personalized analysis can be carried out according to specific requirements of the user, welding process parameter suggestions meeting user expectations are quickly generated, the efficiency of welding process parameter recommendation is effectively improved, and the problems of strong expert experience dependence and relatively high cost in process parameter recommendation are solved.
Owner:BEIJING INST OF TECH
Transport capacity resource recommendation method and device, equipment and storage medium
PendingCN119494482AImprove recommendation efficiencyImprove recommendation accuracyInstrumentsUser needsComputer network
Owner:BEIJING HUITONG TIANXIA LOGISTIC CO LTD
Commodity recommendation method and device, computer equipment, readable storage medium and program product
PendingCN119558940AImprove transaction flexibilityImprove convenienceMachine learningCommerceSoftware engineeringFinancial transaction
The invention relates to a commodity recommendation method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: in response to a transaction recommendation request triggered in a chat interface, displaying a first reply message in the chat interface; inputting a transaction feature based on the first reply message; in response to completion of input of the transaction characteristics, displaying a second reply message in the chat interface, the second reply message comprising a target commodity list; the target commodity list is determined based on the transaction characteristics; and carrying out combined transaction on the commodities in the target commodity list based on a triggering operation on the second reply message. By adopting the method, the matching degree between the target commodity list and the user demand can be improved, and the commodity recommendation accuracy and the commodity recommendation efficiency are improved.
Owner:SHUXING TECH (BEIJING) CO LTD
Article recommendation method and device, electronic equipment and storage medium
PendingCN119415751AImprove recommendation efficiencysave storage spaceNatural language data processingOther databases queryingTheoretical computer scienceEngineering
The embodiment of the invention provides an article recommendation method and device, electronic equipment and a storage medium, and belongs to the technical field of computers. The method comprises the following steps: inputting a plurality of pieces of obtained historical interaction information into a pre-trained word segmentation device, and encoding each piece of historical interaction information to obtain a corresponding encoding feature; calculating the similarity between the coding feature and a plurality of preset codebook vectors to obtain a similarity score, and determining a mapping codeword corresponding to the coding feature based on the similarity score; decoding the mapping code word, determining code word information of the corresponding article according to a decoded result, and determining prefix information corresponding to the code word information; determining an article identifier corresponding to each article according to the code word information and the prefix information; and based on the similarity score, selecting a target identifier from the plurality of article identifiers, and determining an article corresponding to the target identifier as a target recommended article. According to the invention, the item recommendation efficiency can be improved.
Owner:PENG CHENG LAB
Vehicle-mounted APP recommendation method based on user comment emotion elements
PendingCN119622091Aeasy to digcomprehensive descriptionDigital data information retrievalNatural language data processingPersonalizationData pack
Owner:重庆中科汽车软件创新中心
Group and position recommendation method and device based on chat tool, equipment and medium
PendingCN119646301AImprove experienceefficient managementDigital data information retrievalBiological modelsEngineeringData science
The invention discloses a chat tool-based group and position recommendation method and device, equipment and a medium. The method comprises the following steps: creating a plurality of group categories; setting the group attribute of each initial group for a plurality of initial groups created in the chat tool; the group attribute comprises a group attribute name, a target group category to which the group attribute belongs, a matching priority and a matching screening item; according to the matching priority, matching the portrait data of the target user with the group attribute of each initial group in sequence; in the matching process, if the ith initial group is successfully matched and the target user does not join the ith initial group, classifying the ith initial group or a subgroup thereof into a recommendation list; if the target user joins the ith initial group, continuing to match the next matching priority; recommending the group in the recommendation list to the target user; and pushing the target position to the target initial group and / or subgroup successfully matched with the target position. The group recommendation efficiency, the recruitment efficiency and the success rate can be improved.
Owner:QIAN JIN NETWORK INFORMATION TECH SHANGHAI LTD
Literature recommendation method and device based on double-tower model, equipment and medium
PendingCN119669451Aquick responseexact matchDigital data information retrievalSemantic analysisPersonalizationEngineering
The invention relates to the technical field of literature retrieval. The invention discloses a literature recommendation method, device and equipment based on a double-tower model and a medium, and the method comprises the steps: obtaining behavior data of a target user; according to the behavior data of the target user, extracting a behavior preference feature vector of the target user, and calculating a deep representation vector of the target user based on a double-tower model; obtaining a deep representation vector of the candidate literature based on a preset vector database, and calculating the similarity between the deep representation vector of the target user and the deep representation vector of the candidate literature; and generating a literature recommendation list of the target user according to the similarity. According to the method, the semantic features and the interest preference features of the user are obtained by deeply fusing the historical behavior data of the user, a literal matching category is exceeded, user requirements can be more accurately matched, and personalized recommendation is realized. And meanwhile, by utilizing the parallel processing capability of the double-tower model, the response speed of the recommendation system can be increased, and the recommendation efficiency is improved.
Owner:TONGFANG KNOWLEDGE DIGITAL PUBLISHING TECH CO LTD
Multimedia resource recommendation method and device, equipment and storage medium
PendingCN119577238Aquick recommendationImprove convenienceDigital data information retrievalSubstation equipmentEngineeringData science
The invention relates to a multimedia resource recommendation method and device, equipment and a storage medium. The method comprises the steps that multimedia resources are displayed on a resource playing page of a current user account; and in response to an operation instruction of continuous target times triggered for the resource playing page, recommending the multimedia resource to a target user account, the target user account is a user account having a social relationship with the current user account; the time interval between any two adjacent operation instructions in the continuous target number of operation instructions is smaller than a preset threshold value. The diversity of resource recommendation modes is improved, and the recommendation convenience and recommendation efficiency of the multimedia resources are improved.
Owner:BEIJING DAJIA INTERNET INFORMATION TECH CO LTD
Data recommendation method, device, equipment and computer-readable storage medium
ActiveCN114722271BEasy to formulatereduce redundant timeData processing applicationsSpecial data processing applications
The present application discloses a data recommendation method, device, equipment and computer-readable storage medium, which belongs to the field of data processing technology. The method includes: obtaining the search data of the target user; determining the first recommended data corresponding to the search data; obtaining multiple second recommended data related to the first recommended data based on the recommended reference data, and the recommended reference data is obtained based on the historical self-driving data of the target user; and recommending the second recommended data that meets the recommendation conditions among the first recommended data and the multiple second recommended data. The method recommends more recommended data that meet the user's needs to the user based on the user's historical self-driving data, so that the results of data recommendation are more diversified, and through the screening of the recommended conditions, the recommended data is made more accurate, which saves a lot of redundant time, improves the recommendation efficiency, and facilitates the formulation of self-driving routes based on the recommended data.
Owner:BEIJING PHOENIX AUTO INTELLIGENCE CO LTD
Object recommendation interaction method and device, electronic equipment and storage medium
PendingCN119597192Aimprove noveltyImprove effectivenessDigital data information retrievalSpecial data processing applicationsComputer hardwareComputer graphics (images)
The invention relates to an object recommendation interaction method and device, electronic equipment and a storage medium. The method comprises the steps that recommended media content corresponding to a target object is displayed on a preset page; in the recommended media content display process, displaying a first part of picture in a first preset recommended picture corresponding to the target object in a preset area in a preset page, and displaying a second part of picture in the first preset recommended picture in the preset page; in response to a preset interaction operation triggered by the target account, moving the second part of the picture to a first preset sub-region in the preset region to enable the preset region to display a complete first preset recommended picture; and skipping to an associated page corresponding to the target object under the condition that the complete first preset recommendation picture is displayed. By utilizing the embodiment of the invention, the presentation style of the object recommendation picture can be enriched, the effectiveness and interestingness of user interaction are improved, the user interaction experience is improved, and the object recommendation effect and the object recommendation efficiency are improved.
Owner:BEIJING DAJIA INTERNET INFORMATION TECH CO LTD
A personal and group-oriented behavior internet modeling and prediction recommendation method
ActiveCN117076768BImprove recommendation efficiencyImprove recommendation effectBiological modelsOther databases indexingPersonalizationEngineering
The application discloses a kind of individual and group-oriented behavior internet modeling and prediction recommendation method, the method includes the following steps: step 1: establish the behavior preference model of behavior internet based on hypergraph;Step 2: extract the relationship between behaviors based on the model of step 1;Step 3: discover the behavior mode of user based on the behavior relationship of step 2;Step 4: predict the behavior trend of user based on the behavior relationship of step 2 and the behavior mode of step 3;Step 5: personalized service recommendation is carried out for user based on step 2, step 3, step 4.The model of behavior internet is proposed in the application, and the personalized behavior internet is obtained by cause-effect inference and relationship discovery, and the recommendation is carried out by using the deep learning method based on external knowledge, which improves the recommendation efficiency and effect for individual and group, overcomes the shortcomings that the traditional recommendation method based on deep learning is difficult to fully utilize personalized knowledge, and realizes the personalized and efficient recommendation of service.
Owner:HARBIN INST OF TECH
Recommended processing method, apparatus, device, storage medium and program product
ActiveCN116861065BImprove recommendation efficiencyImprove recommendation accuracyDigital data information retrievalSpecial data processing applicationsPersonalizationEngineering
This application provides a recommendation processing method, apparatus, electronic device, computer-readable storage medium, and computer program product based on artificial intelligence. The method includes: acquiring the interaction features and object features of a target account; performing first attention processing on the interaction features based on a first object interest pool to obtain interaction interest features, and performing second attention processing on the object features based on a second object interest pool to obtain object interest features; acquiring the activity features of the target account, and performing selection processing on the interaction interest features and object interest features based on the activity features to obtain recall features of the target account; based on the recall features and the information features of the information to be recommended, obtaining target information from the information to be recommended, and performing a recommendation operation on the target account based on the target information. This application enables accurate personalized recommendations and improves recommendation processing efficiency.
Owner:TENCENT TECHNOLOGY (SHENZHEN) CO LTD
Video recommendation method, device, apparatus and storage medium
ActiveCN115757864BImprove recommendation effectsave storage spaceDigital data information retrievalSpecial data processing applicationsPattern recognitionComputer vision
This application provides a video recommendation method, apparatus, device, and storage medium, relating to the field of communication technology. The method includes: upon receiving a video acquisition request, acquiring a candidate video list; acquiring the interaction probability between the user and each candidate video in the candidate video list, the interaction probability being determined based on the user's reconstructed embedding vector and the candidate video's reconstructed embedding vector; the user's reconstructed embedding vector being determined based on the user's embedding vector, the user's feature vector, and a pre-trained vector reconstruction model; the candidate video's reconstructed embedding vector being determined based on the candidate video's embedding vector, the candidate video's feature vector, and the vector reconstruction model; simulating the input of sample data during cold start when training the vector reconstruction model; and determining the target video to recommend to the user from the candidate video list based on the interaction probability between the user and each candidate video in the candidate video list. This method can accurately recommend videos to users during cold start, improving the video recommendation effect during cold start.
Owner:TENCENT TECHNOLOGY (SHENZHEN) CO LTD
Text word recommendation method, device, electronic device and readable storage medium
ActiveCN114064877Bimprove accuracyImprove recommendation efficiencyDigital data information retrievalSemantic analysis
The present invention discloses a method, device, electronic device and readable storage medium for recommending text words and sentences. The method comprises: obtaining a keyword or a key sentence, wherein the keyword or the key sentence is a keyword or a key sentence selected in the text, or a keyword or a key sentence obtained in an input box; performing recommendation prediction on the keyword or the key sentence to obtain M recommended words and sentences; screening out N candidate words and sentences that meet preset screening conditions from the M recommended words and sentences; and displaying the N candidate words and sentences. The above scheme realizes the convenience and intelligence of text word and sentence recommendation and improves the accuracy of text word and sentence recommendation.
Owner:BEIJING SOGOU TECHNOLOGY DEVELOPMENT CO LTD
Media content processing method and device, electronic equipment and storage medium
ActiveCN119450157AImprove recommendation efficiencyImprove recommendation effectSelective content distributionComputer hardwareMediaFLO
The invention relates to a media content processing method and device, electronic equipment and a storage medium. The method comprises the steps that a task issuing interface which corresponds to a preset task and comprises at least one task configuration control is displayed; the preset task is a task which cooperates with the task publisher and provides media content corresponding to the task publisher to the target browsing account; in response to a task configuration instruction triggered based on any task configuration control, displaying task configuration information corresponding to the task configuration instruction on a preset release interface; and in response to a task publishing instruction of the target task publisher for the target media content, based on at least one piece of task configuration information configured in the preset publishing interface, publishing a preset task corresponding to the target media content, so that at least one task browser applies for a task processing permission of the preset task corresponding to the target media content. According to the embodiment of the invention, the distribution efficiency can be greatly improved on the basis of meeting diversified distribution requirements.
Owner:BEIJING DAJIA INTERNET INFORMATION TECH CO LTD
Model training method and device, model recommendation method and device, medium, product and equipment
PendingCN119622087Aimprove accuracyreduce training timeDigital data information retrievalCommerceInformation processingData pack
The invention relates to the technical field of information processing, and provides a training method of a resource recommendation model, a resource recommendation method and device, a computer readable medium and electronic equipment. The resource recommendation model training method comprises the steps of obtaining sample data and label data corresponding to the sample data, wherein the sample data comprises first historical consumption behaviors of different users on resources of a target type; determining a heterogeneous resource behavior sequence corresponding to the sample data based on historical operation behaviors, indicated by the sample data, of the user on various different types of resources before the first historical consumption behavior; determining a resource vector corresponding to a resource in the heterogeneous resource behavior sequence, and obtaining a heterogeneous resource sequence feature of the heterogeneous resource behavior sequence; and obtaining resource features of the to-be-recommended resources of the target type, and training an initial resource recommendation model according to the heterogeneous resource sequence features, the resource features and the tag data to obtain the resource recommendation model. According to the scheme, the accuracy of resource recommendation can be improved.
Owner:HANGZHOU NETEASE CLOUD MUSIC TECH CO LTD
Video recommendation method, device and equipment and readable storage medium
PendingCN119557476AImprove personalizationImprove targetingMetadata video data retrievalSelective content distributionPersonalizationEngineering
Owner:E-SURFING DIGITAL LIFE TECH CO LTD
Video recommendation method, apparatus, device, and storage medium
This application provides a video recommendation method, apparatus, device, and storage medium, relating to the field of communication technology. The method includes: upon receiving a video acquisition request, acquiring a candidate video list; acquiring the interaction probability between the user and each candidate video in the candidate video list, the interaction probability being determined based on the user's reconstructed embedding vector and the candidate video's reconstructed embedding vector; the user's reconstructed embedding vector being determined based on the user's embedding vector, the user's feature vector, and a pre-trained vector reconstruction model; the candidate video's reconstructed embedding vector being determined based on the candidate video's embedding vector, the candidate video's feature vector, and the vector reconstruction model; simulating the input of sample data during cold start when training the vector reconstruction model; and determining the target video to recommend to the user from the candidate video list based on the interaction probability between the user and each candidate video in the candidate video list. This method can accurately recommend videos to users during cold start, improving the video recommendation effect during cold start.
Owner:TENCENT TECHNOLOGY (SHENZHEN) CO LTD
Label generation model training method, label generation method, device and equipment
ActiveCN115905621BInterestedImprove experienceMetadata video data retrievalCharacter and pattern recognitionComputer graphics (images)The Internet
The application provides a label generation model training method, a label generation method, a device and equipment, and belongs to the technical field of Internet. The method comprises the following steps: acquiring a sample quadruple; encoding a sample video based on a label generation model to obtain a sample video feature, wherein the label generation model is used for generating a character label for a video based on the video, a character name of a character in the video and a face feature; predicting the sample video feature, the sample character name and the sample face feature based on the label generation model to obtain a prediction result; and training the label generation model based on the difference between the prediction result and sample supervision information. The above technical solution enables the trained label generation model to determine a label suitable for a video, and then enables the label to be used for video recommendation for a viewing object, so that the recommended video is more in line with the interest of the viewing object, the recommendation efficiency is improved, and the experience of the viewing object is improved.
Owner:TENCENT TECHNOLOGY (SHENZHEN) CO LTD
Commercial tenant recommendation method of platform, electronic equipment, storage medium and program product
PendingCN119539915Aimprove accuracyImprove recommendation efficiencyDigital data information retrievalCommerceEngineeringBehavioral data
The embodiment of the invention provides a platform merchant recommendation method, electronic equipment, a storage medium and a program product. The method comprises the steps of obtaining first historical behavior data when a current user interacts with a platform, and determining an initial recommendation basis of the current user according to the first historical behavior data; according to the first historical behavior data and a pre-constructed reference basis recommendation pool, determining a reference recommendation basis of the current user; wherein the reference basis recommendation pool is a data pool which is pre-constructed based on a large model according to second historical behavior data when a historical user interacts with the platform and is used for determining a reference recommendation basis of the current user; determining a final recommendation basis of the current user according to the initial recommendation basis and the reference recommendation basis; and according to the final recommendation basis, determining and presenting at least one to-be-recommended merchant. The method is used for achieving the effect of improving the accuracy and efficiency of merchant recommendation of the platform.
Owner:CHINA UNIONPAY
Education resource sequence recommendation method and device based on three-view structure distillation, equipment and storage medium
ActiveCN121834065BEfficient captureEffective portrayalDigital data information retrievalBiological modelsRecommendation modelEngineering
The application discloses a kind of education resource sequence recommendation method, device and equipment based on three-view structure distillation and storage medium, the method includes: based on student-course interaction log, the learning sequence of time sequence course index is constructed, three types of view hypergraph are constructed according to semantic, path, concept structure multidimensional feature, three-view course representation matrix is generated by structure coding fusion, and the recommended list is output by inputting education resource recommendation model;Education resource recommendation model generates student state vector by the coding of Transformer, and the total course score is obtained by fusing three-view branch score and predicted;The present application predicts the education resource recommendation by three-view collaborative scoring from multiple perspectives, accurately captures course representation, effectively depicts learning path high-order law, improves the accuracy, explainability and generalization ability of education resource recommendation in sparse interaction and cold start scene.
Owner:湖南工商大学
Information display method and device and related product
PendingCN119576178AImprove recommendation efficiencyCommerceInput/output processes for data processingComputer graphics (images)Engineering
The embodiment of the invention provides an information display method and device and a related product, and the method comprises the steps: displaying at least one column of information flow in a first page, and displaying first recommendation content in the information flow; the first recommendation content is generated based on first published content; the first published content comprises a first post belonging to a first topic and / or a first comment related to a first electronic book; the first topic is related to the first electronic book; in response to a trigger operation for the first recommendation content, displaying a second page; the second page comprises a first display area and a second display area; the first display area is used for displaying an image related to the first electronic book, and the second display area is at least used for displaying the first published content.
Owner:DOUYIN VISION CO LTD
Label generation model training method, label generation method, device and equipment
The application provides a label generation model training method, a label generation method, a device and equipment, and belongs to the technical field of Internet. The method comprises the following steps: acquiring a sample quadruple; encoding a sample video based on a label generation model to obtain a sample video feature, wherein the label generation model is used for generating a character label for a video based on the video, a character name of a character in the video and a face feature; predicting the sample video feature, the sample character name and the sample face feature based on the label generation model to obtain a prediction result; and training the label generation model based on the difference between the prediction result and sample supervision information. The above technical solution enables the trained label generation model to determine a label suitable for a video, and then enables the label to be used for video recommendation for a viewing object, so that the recommended video is more in line with the interest of the viewing object, the recommendation efficiency is improved, and the experience of the viewing object is improved.
Owner:TENCENT TECHNOLOGY (SHENZHEN) CO LTD
Resource recommendation method and device, electronic equipment, storage medium and program product
PendingCN119669552AImprove recommendation efficiencyreduce consumptionDigital data information retrievalAdvertisementsData miningDatabase
The embodiment of the invention provides a resource recommendation method and device, electronic equipment, a storage medium and a program product, and relates to the technical field of artificial intelligence and cloud. The method comprises the steps of obtaining at least one first resource to be recommended to a target object, and determining a first resource fingerprint of each first resource in the at least one first resource; then obtaining a resource fingerprint pre-estimation group corresponding to at least one second resource set related to the target object, wherein the resource fingerprint pre-estimation group comprises a target resource fingerprint and a target pre-estimation value; then, for each first resource, matching the first resource fingerprint with the target resource fingerprint of each resource fingerprint pre-estimation group; and under the condition that the first resource fingerprint of the first resource is successfully matched with the target resource fingerprint of one resource fingerprint estimation group, recommending a target resource in the at least one first resource to the target object. According to the embodiment of the invention, the computing power resource consumption for calculating the estimated value can be reduced, so that the resource recommendation efficiency is improved.
Owner:BEIJING SOGOU TECHNOLOGY DEVELOPMENT CO LTD
Dynamic recommendation method and device for media content, equipment and medium
PendingCN119622017Aavoid one-sidednessavoid limitationsWeb data indexingSpecial data processing applicationsMediaFLOEmotion identification
The invention provides a dynamic recommendation method for media content, which is applied to the financial field and comprises the following steps: responding to a request of a target user for acquiring a to-be-recommended media text, and acquiring target voice information of the target user; extracting target voiceprint information of the target voice information, determining behavior information and attribute information of the target user, and constructing an initial user portrait according to the behavior information and the attribute information; inputting the target voice information into a trained emotion recognition model, performing emotion spectrum analysis on the target voice information to obtain a real-time emotion, and constructing a real-time user portrait according to the real-time emotion and the initial user portrait; identifying a keyword of the target voice information, and crawling a preset number of media texts from a preset page by using the keyword to obtain a media text set; and selecting a media text from the media text set according to the real-time user portrait for recommendation.
Owner:PING AN TECH (SHENZHEN) CO LTD
Enterprise Recommended Methods, Apparatus, Equipment and Storage Media
ActiveCN116070023BImprove recommendation efficiencyWebsite content managementKnowledge representation
This specification discloses a method, apparatus, device, and storage medium for enterprise recommendation. The method includes: obtaining an enterprise recommendation request from an enterprise, the enterprise recommendation request carrying enterprise information of the enterprise, the enterprise information representing the enterprise's products and its role in the industry chain, and the enterprise recommendation request requesting recommendations of partner enterprises to the enterprise; structuring the enterprise information to obtain product entities and enterprise role entities in the enterprise information; querying an industry graph based on the product entities to obtain multiple candidate partner enterprises, the industry graph including multiple enterprises belonging to different industry chains, the multiple candidate partner enterprises belonging to the same industry chain as the enterprise; and determining a target partner enterprise to recommend to the enterprise from the multiple candidate partner enterprises based on the enterprise role entities.
Owner:ALIPAY (HANGZHOU) INFORMATION TECH CO LTD
Offline item recommendation method, device, equipment and storage medium
ActiveCN116562982BImprove experienceRecommended results are accurateDigital data information retrievalBiological modelsEngineeringSmart technology
The present invention provides an offline item recommendation method, device, equipment and storage medium, which relates to the field of artificial intelligence technology. The method includes: obtaining the user's interactive item sequence at the current moment; using the trained first action value network to calculate the action value of all items in the interactive item sequence; the action value represents the user's preference for the item; the first action value network is obtained by training in an offline environment; and the item corresponding to the largest action value among the action values of all items is determined as the recommended item. The method provided by the present invention has a high recommendation efficiency, and because the first action value network is trained in an offline environment, that is, the first action value network can be trained without interacting with the real recommendation environment, the recommendation results of the trained first action value network are more accurate and the user experience is better.
Owner:TSINGHUA SHENZHEN INTERNATIONAL GRADUATE SCHOOL
Strategy model training method and device, content sorting method and device and computer equipment
PendingCN119622102AAdjust in timeimprove accuracyDigital data information retrievalInternal combustion piston enginesEngineeringData mining
The invention relates to a strategy model training method and device, a content sorting method and device and computer equipment. The method comprises the following steps: determining a plurality of sample user state representations based on user information obtained in a historical time period; determining a value label corresponding to each sample user state representation based on a plurality of recommended contents in a historical time period; respectively inputting the plurality of sample user state representations into a trained model, and determining sample responses of the sample user state representations for the plurality of recommended contents in the historical time period according to an output result of the trained model; and optimizing model parameters of the trained model according to the plurality of sample user state representations, the plurality of sample responses and the plurality of value labels to obtain a strategy model. By adopting the method, the recommendation efficiency and the recommendation effect can be improved.
Owner:XINGIN INFORMATION TECH (SHANGHAI) CO LTD
Project team employee-suitable-for-post recommendation method and device
The invention relates to the technical field of data analysis and application, in particular to a project team post-suitable employee recommendation method and device, and the method comprises the steps: receiving team demand information of project building and employee information of to-be-evaluated employees, and the team demand information at least comprises target post information; according to the employee information of the to-be-assessed employee, performing matching from a post label model associated with a target post to obtain ability label information of the to-be-assessed employee; according to the ability label information of the to-be-assessed employee, calculating to obtain an appropriate post matching degree corresponding to the to-be-assessed employee; and according to the target post information and the post-suitable matching degree corresponding to the to-be-evaluated employee, determining post-suitable employee recommendation information. According to the method, the employees suitable for the job can be automatically recommended, and the problems of difficult employee recommendation and low efficiency during existing project team establishment are solved.
Owner:SHANGHAI PUDONG DEVELOPMENT BANK
Product recommendation method and device, electronic equipment and storage medium
PendingCN121959434AReduce real-time callsreduce dependenceSpecial data processing applicationsText database clustering/classificationBehavioral dataSmart technology
The embodiment of the invention provides a product recommendation method and device, electronic equipment and a storage medium, belongs to the technical field of artificial intelligence, and is suitable for the field of financial science and technology. The method comprises the steps of obtaining a target consultation text from a target object and original behavior data of the target object; performing user classification on the target object according to the original behavior data to obtain a target group type of the target object; screening out a target product type from preset original product types according to the target consultation text; selecting reference data from the target product type and the target consultation text according to the target group type, and performing product matching according to the target group type and the reference data to obtain a target product; and recommending the target product to the target object. According to the embodiment of the invention, the product recommendation efficiency can be improved.
Owner:PING AN TECH (SHENZHEN) CO LTD