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43results about How to "Precise personalized recommendation" patented technology
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Association-rule recommending method based on self-adaptive multiple minimum supports
ActiveCN103700005APrecise personalized recommendationReduce sparsityMarketingPersonalizationValue set
The invention discloses an association-rule recommending method based on self-adaptive multiple minimum supports. The method comprises the following steps of firstly, establishing a commodity-classifying hierarchical tree according to commodity classification, and classifying concrete commodities according to the classifying hierarchical tree; next respectively carrying out minimum-support threshold-value setting on each concrete commodity and the upper-layer class of a concrete-commodity layer, and then mining frequent item sets and generating rules by utilizing a multiple-minimum-support association-rule expanding algorithm on the basis of the support threshold-value setting, wherein the threshold-value setting relates to the influences of time factors, concrete-commodity price factors and concrete-commodity brand factors; finally generating recommendation for each user by adopting a TOP-N recommending method. When personalized recommendation is made for the user by the association-rule recommending method, the characteristics of different objects can be better embodied by considering the influences of many factors on the multiple-minimum-support threshold-value setting for the concrete commodities and the classes; meanwhile, a data-sparsity problem and a cold-starting problem in a recommending system are relieved, so that the personalized recommendation can be more accurately made for the user.
Owner:SHANGHAI ZHENKE BUSINESS CONSULTING CO LTD
Real-time goods recommendation method based on customer shopping intention exploration
InactiveCN102800006AImprove satisfactionPrecise personalized recommendationMarketingPersonalizationTree shaped
The invention discloses a real-time goods recommendation method based on customer shopping intention exploration. The method comprises the following steps: 1, constructing a tree-shaped customer shopping intention model; 2, detecting user behaviors in real time and identifying user intention; 3, detecting the change of the user intention in real time; 4, tracking the change track of the user intention and predicting the deep intention of the user: predicting the deep intention of the user based on the discrete intention of the user; and 5, determining a goods recommendation strategy: determining the goods recommendation strategy according to the shopping intention of the customer. The method disclosed by the invention automatically identifies the shopping intention of the customer, performs precise individualized recommendation, and improves the customer satisfaction; and moreover, the method automatically detects the change of the shopping intention of the customer and adjusts the goods recommendation strategy. The method adapts to the changing interest of the customer in real time, deeply explores the shopping intention of the customer based on the user intention model and provides professional recommendation service to the user.
Owner:姚明东
Recommendation method and device based on artificial intelligence, electronic equipment and storage medium
ActiveCN111291266APrecise personalized recommendationMathematical modelsDigital data information retrievalEngineeringArtificial intelligence
The invention provides a recommendation method and device based on artificial intelligence, electronic equipment and a storage medium. The method comprises the steps of obtaining object features of ato-be-recommended object and candidate recommendation information features of each piece of candidate recommendation information, and combining the object features with the candidate recommendation information features of each piece of candidate recommendation information to form fusion features corresponding to each piece of candidate recommendation information; performing multi-level mapping processing on the fusion feature corresponding to each piece of candidate recommendation information to obtain scores of each piece of candidate recommendation information corresponding to a plurality ofindexes; performing multi-index aggregation processing on the scores corresponding to the plurality of indexes to obtain a comprehensive score of each piece of candidate recommendation information soas to perform descending sorting on the plurality of pieces of candidate recommendation information; and selecting at least one piece of candidate recommendation information sorted in the top from adescending sorting result to execute a recommendation operation corresponding to the to-be-recommended object. According to the invention, accurate recommendation of information can be realized.
Owner:深圳市雅阅科技有限公司
Information recommendation system and method
ActiveCN107562818AImprove accuracyPrecise personalized recommendationSpecial data processing applicationsData warehouseUnstructured data
The invention provides an information recommendation system and method. The system comprises a basic data collection device, a data warehouse processing device, a basic recommendation engine device and a recommendation engine optimization device, wherein the basic data collection device is used for collecting the historical data of client browsing information and purchasing information from a financial enterprise system, wherein the historical data comprises structured data and unstructured data; the data warehouse processing device is used for receiving the historical data, converting the unstructured data into the structured data and carrying out data cleaning processing on the converted structured data and unstructured data; the basic recommendation engine device is used for calculatinga relationship between a client and a preference commodity according to the client browsing information and purchasing information in the historical data subjected to the data cleaning processing inpreset time, and obtaining a preliminary recommendation result according to the relationship between the client and the preference commodity; the recommendation engine optimization device is used forregulating the preliminary recommendation result according to a recommendation accuracy optimization regulation factor to obtain a final recommendation result, and providing the final recommendation result for a client side server. By use of the above technical scheme, information recommendation accuracy is improved.
Owner:INDUSTRIAL AND COMMERCIAL BANK OF CHINA
Matrix decomposition recommending method and system based on extended label
ActiveCN107239993AImprove calculation accuracyPrecise personalized recommendationBuying/selling/leasing transactionsPersonalizationQR decomposition
The invention discloses a matrix decomposition recommending method based on an expanded label, comprising: constructing an item-label matrix based on the item label data and calculating the label similarity; constructing a first item pair-label vector based on the item-label matrix; and according to the label similarity, extending the first item pair label-vector as a second item pair-label vector; establishing an item similarity matrix based on the second item pair-label vector; solving a user implicit characteristics matrix and an item implicit characteristics matrix based on the item similarity matrix and the pre-constructed item scoring matrixes; predicting the score by the user to the unrated items; and building a list of recommended items for the user. At the same time, the invention also discloses a matrix decomposition recommending system based on the expanded label. The invention can provide the user with more accurate personalized recommendations when the label is sparse, and relieves the problem of cold starting of the item to a certain extent.
Owner:HAINAN UNIVERSITY
News recommendation method and device
ActiveCN106484760APrecise personalized recommendationImprove experienceSpecial data processing applicationsPersonalizationKeyword analysis
The embodiment of the invention provides a news recommendation method. The news recommendation method comprises the steps of monitoring an operation behavior of a user in a news browsing page; when a preset operation behavior is monitored, triggering to start a voice collection device; performing keyword analysis on collected voice; and determining news which the user is currently interested in and recommending the news to the user based on the keyword obtained through analysis. The user when browsing the news can trigger to start the voice collection device through the preset operation behavior, so that the current reading interestingness can be fed back through voice, the current reading interestingness of the user can be analyzed and the corresponding news can be determined and recommended to the user based on the user voice, and more accurate individual recommendation for the user can be carried out; furthermore, the operation is convenient, the reading efficiency is increased, and better experience is brought to the user. In addition, the embodiment of the invention provides a news recommendation device.
Owner:NETEASE MEDIA TECH BEIJING
Catering resource recommendation method based on video application and system thereof
InactiveCN107016567APrecise personalized recommendationImprove experienceMetadata video data retrievalBuying/selling/leasing transactionsPersonalizationResource information
The invention relates to a catering resource recommendation method based on a video application and a system thereof and belongs to the information pushing field. A problem that routine video application pushing information does not match with a user demand so that a user experience is poor is solved. The method is characterized by acquiring characteristic information of a user when the user operates the video application, and according to the characteristic information, acquiring a plurality of characteristic labels of the user; matching the plurality of characteristic labels of the user with a plurality of preset characteristic labels of catering resources in a catering resource database one by one so as to acquire a matching degree of the user and the catering resources in the catering resource database; and according to the matching degree of the user and the catering resources in the catering resource database, screening the catering resources suitable for the user and pushing to the user. The method and the system are used for accurately recommending catering resource information to the user in a customized mode, an experience of the user to use the video application is increased and maneuverability of the video application is enhanced.
Owner:CHENGDU STARCOR INFORMATION TECH
Video clip recommendation method based on graph convolution network
ActiveCN110837578AOvercome the problem of sparsityPrecise personalized recommendationDigital data information retrievalNeural architecturesAlgorithmComputer vision
The invention discloses a video clip recommendation method based on a graph convolution network. The video clip recommendation method comprises the steps of 1, constructing a scoring matrix of a userfor video clips; 2, processing the user set and the video clip set to obtain a user embedding matrix and a video clip embedding matrix; 3, constructing a bipartite graph based on content attributes according to the score matrix of the user; 4, inputting the constructed bipartite graph into a graph convolution network, and continuously updating a user embedding matrix; and 5, calculating a preference prediction value of the user for the segment by utilizing a graph convolution network, thereby recommending the segment to the user. According to the method, more accurate recommendation can be carried out on the user, especially for a user group with few historical data, so that the problem of cold start of an article is better solved.
Owner:HEFEI UNIV OF TECH
Collaborative filtering recommendation method of theme based on viewpoint enhancement
InactiveCN108228867AGood robustnessPrecise personalized recommendationBuying/selling/leasing transactionsSpecial data processing applicationsViewpointsScoring methods
The invention discloses a collaborative filtering recommendation method of a theme based on viewpoint enhancement. The method includes the steps that first, comment text attribute words are extractedbased on an LDA theme model; then, the similar attribute words are classified as one category by utilizing a word2vec model to calculate relations among the attribute words based on the attribute words extracted by the LDA; the attribute words with the same meanings are collected as an attribute surface; the sentiment polarity of comment texts is obtained through the analysis of attribute surfaceviewpoint enhancement; next, a scoring matrix is constructed according to the polarity of sentiment words and attribute words, and the similarity among users is calculated according to a scoring method and through a collaborative filtering algorithm; finally, goods with high scores in the matrix are recommended to other users according to a k-nearest neighbor algorithm. Experimental results show that the collaborative filtering recommendation method is excellent in F value extracted by attribute words and mean absolute error of recommendation.
Owner:WUHAN UNIV
Collection method and apparatus of television user behavior information
InactiveCN105635795AImprove collection efficiencyHigh degree of automationSelective content distributionTelevision equipmentCollection methods
The disclosure relates to a collection method and apparatus of television user behavior information. The method comprises: when television equipment plays a television program, an image collection device collects user image information of a first user watching the television program by the television equipment in real time, and / or an audio collection device collects user audio information of the first user watching the television program by the television equipment in real time; the user image information and / or the user audio information are / is identified to obtain basic description information of the first user; and a correspondence relation between the basic description information of the first user and television program information of the television program is stored into a user behavior database. Therefore, the information collection efficiency, the automation degree and the accuracy are high.
Owner:XIAOMI INC
Intelligent news recommendation system based on emotion protection
PendingCN113343120AMonitor emotional levelPrecise personalized recommendationMathematical modelsData processing applicationsCluster algorithmFeature vector
The invention provides an intelligent news recommendation system based on emotion protection. A method comprises the following steps: 1, extracting news features and text feature words by utilizing a BERT pre-training model, and constructing a news feature matrix through news feature vectors; 2, performing emotion filtering on the text information to establish an emotion grading model, and performing emotion grading on user comments, news titles and contents to distinguish negative and positive degrees; 3, clustering news labels through a clustering algorithm, distributing weights to news browsed by users according to user comment emotion levels and user behavior time, and constructing a user matrix according to user feature information; 4, predicting the emotion level of the user in the next time period according to the time sequence of the user emotion; and 5, generating a recommendation table by calculating the similarity between the user and the news vector, predicting the emotional state of the user, and recommending the news in proportion by using a Bayesian method to realize dynamic pushing. According to the invention, negative energy and negative public opinions are prevented from hurting the psychology of the user and harming the public safety of the society.
Owner:HARBIN UNIV OF SCI & TECH
Personalized recommendation method and system based on improved clustering and Spark framework
InactiveCN110020141AAchieve parallelizationReduce sparsityDigital data information retrievalCharacter and pattern recognitionPersonalizationData set
The invention discloses a personalized recommendation method based on improved clustering and a Spark framework. The personalized recommendation method comprises the steps of determining an effectivescoring data set; performing clustering preprocessing on the project by utilizing a Canopy algorithm to generate at least one Canopy clustering center; initializing a clustering center of the FCM algorithm, updating the membership degree of each project to the clustering center by using a membership degree calculation formula, updating the clustering center according to the updated membership degree, and performing iteration until a stop condition is met, and determining a final clustering set; respectively calculating the similarity between the target project and each clustering center in thefinal clustering set, selecting projects in the clustering set corresponding to the similarity greater than or equal to a preset similarity threshold to form a candidate project space, calculating the similarity between the target project and each project in the candidate project space, and searching a K nearest neighbor set of the target project; obtaining a preference prediction value of the user for the target project, and using the top-N recommendation method to select N items with higher preference prediction values for recommendation..
Owner:AEROSPACE INFORMATION
Personalized diet recommendation method and system based on knowledge graph
PendingCN112818222AAccurate recommendationPrecise personalized recommendationSemantic analysisSpecial data processing applicationsPersonalizationBehavioral data
The invention discloses a personalized diet recommendation method and system based on a knowledge graph. The method comprises the steps: acquiring menu data of a knowledge base, extracting attribute information of a menu, and constructing a menu entity node; acquiring existing user historical behavior data, calculating similarity between menus, and generating a menu knowledge graph according to the similarity; according to the menu knowledge graph, generating a first recommendation candidate set with high similarity with the historical behavior data of the user; calculating the tendency degree of the user to the menu attributes, and generating a relation graph of the user and the menu attributes; screening out an optimized second recommendation candidate set according to a relation graph of the user and menu attributes; calculating and generating a relation graph between the users according to the relation graph between the users and the menu attributes; and generating a final recommendation candidate list according to the relation graph between the users and the collection behaviors of the target similar users. According to the method, layer-by-layer recommendation list screening is carried out based on the multiple knowledge graphs, and accurate personalized recommendation is realized.
Owner:吾征智能技术(北京)有限公司
A pushing system for academic conference papers based on data mining
InactiveCN109213908APrecise personalized recommendationInstant accessWeb data indexingNatural language data processingResearch efficiencyPersonalization
The invention relates to a pushing system for academic conference papers based on data mining, which comprises a user login registration module for user registration and login, and a system for modifying and saving user information through a database. The data capture module is used for crawling relevant paper information from the designated conference website by using Webmagic open source tool; paper browsing and recording module, used for browsing, searching, collection, note-taking and message functions; paper update detection and new paper detection module, which is used to regularly monitor the update of papers on the conference website; the paper pushing module is used for triggering the mail pushing task every day when a new paper is detected or a recommended paper is needed for production. The personalized recommendation module is used for inferring the papers that the user may like according to the historical data of the user. The invention frees researchers from complicated and time-consuming activities of searching and tracking papers and improves scientific research efficiency.
Owner:ZHEJIANG UNIV OF TECH
Information Recommendation System and Method
ActiveCN107562818BImprove accuracyPrecise personalized recommendationDatabase management systemsSpecial data processing applicationsData packData warehouse
Owner:INDUSTRIAL AND COMMERCIAL BANK OF CHINA
Single-classification collaborative filtering method based on user personality hierarchical structure
ActiveCN110413880APrecise personalized recommendationAlleviate the sparsity problemDigital data information retrievalBuying/selling/leasing transactionsPersonalizationMatrix decomposition
The invention provides a single-classification collaborative filtering method based on a user personality hierarchical structure, and relates to the field of computer data processing. The method for applying the user personality hierarchical structure to the single-classification collaborative filtering algorithm provided by the invention is suitable for processing implicit feedback data. A traditional single-classification collaborative filtering method does not have a hierarchical structure fused with a user; according to the method provided by the invention, based on weighted matrix decomposition, users are layered by introducing personality trait information, a layered structure of the users is constructed, existing information is fully utilized, the problem of data sparseness is relieved, and the unfriendliness of a recommendation system to new users is reduced, so that personalized recommendation of commodities to the users is more accurate.
Owner:HEFEI UNIV OF TECH
Recommended content determination method and device and storage medium
InactiveCN112765450APrecise personalized recommendationDigital data information retrievalAdvertisementsNetwork modelPersonalization
The embodiment of the invention relates to a recommendation content determination method and device and a storage medium. The method comprises the steps of determining predicted click probabilities corresponding to multiple to-be-recommended contents corresponding to a user according to a predicted neural network model, and sorting the multiple to-be-recommended contents according to the predicted click probabilities to determine target recommended contents. According to the invention, the technical problem that accurate personalized recommendation cannot be carried out for new contents and new users due to the fact that a recommendation system in the related technology cannot carry out modeling on the new contents and the new users is solved.
Owner:SENSOR NETWORKS TECH BEIJING CO LTD
User browsing behavior reporting method and device, readable storage medium and electronic equipment
ActiveCN111625712AAvoid the disadvantages of reporting to the serverPrecise personalized recommendationSpecial data processing applicationsWeb data browsing optimisationInformation repositoryPersonalization
The invention relates to a user browsing behavior reporting method and device, a readable storage medium and electronic equipment. The method comprises the steps: traversing an information base to determine a target display area meeting reporting conditions at least according to display state records, recorded in the information base, of all display areas, wherein the reporting conditions at leastcomprise that part of the display areas are displayed; and in response to the determined target display area, reporting user browsing behavior information, the user browsing behavior information at least comprising target display data associated with the target display area. According to the method, the defect that the display data which is not truly seen by the user is reported to the server canbe effectively avoided, the accuracy of analyzing user preferences by the server is improved, the server can accurately perform personalized recommendation for the user, and the browsing experience of the user is improved. Moreover, the process of determining whether the display area meets the reporting condition by the terminal is independent of the browsing operation of the user on the page, sothat the process of determining the target display area meeting the reporting condition is simplified.
Owner:BEIJING SANKUAI ONLINE TECH CO LTD
Fragmented knowledge intelligent aggregation method
ActiveCN108280153AHigh description accuracyPrecise personalized recommendationSpecial data processing applicationsText database clustering/classificationConfidence measuresData science
The invention relates to a fragmented knowledge intelligent aggregation method. The method comprises the steps that step 1, knowledge element ontologies are defined; step 2, fragmented knowledge ontology associated aggregation is defined; step 3, associated aggregation rules based on ontology implication are established; step 4, the determination of aggregation associated rules is conducted; step5, the determination of fragmented knowledge associated rules based on the knowledge element ontologies is conducted; step 6, fragmented knowledge aggregation associated discovery is conducted; step 7, fragmented knowledge aggregation is achieved. According to the method, the associated relationship between two or more knowledge element ontologies is determined through supporting and confidence level determination, and fragmented knowledge aggregation is achieved through a strong associated method; fragmented knowledge characteristics are analyzed by the method, facing the demands of online study, original solid knowledge structures are repartitioned and dynamically aggregated into a knowledge cluster with a self-organizing capability to finally complete fragmented knowledge aggregation, and learners are guided to fully utilize fragmented time to accurately acquire meaningful knowledge contents.
Owner:TIANJIN UNIVERSITY OF SCIENCE AND TECHNOLOGY
Recommendation method based on explicit information coupling analysis of bidirectional long-short-term memory network
InactiveCN112256859AQuality improvementPrecise personalized recommendationDigital data information retrievalNeural architecturesPersonalizationData set
The invention discloses a recommendation method based on explicit information coupling analysis of a bidirectional long-short-term memory network. The recommendation method comprises the steps of dataacquisition and processing, data set division, coupling model construction, model training and project recommendation. According to the method, a BiLSTM bidirectional long-short term memory network and an Attention attention mechanism are combined by analyzing a microscopic coupling relationship between explicit short text information related to a user and a project to obtain explicit text feature representation fused with important context information, and the explicit text feature representation is combined with implicit features to obtain an explicit text feature representation model. Thecoupling relation between the comment text information and the subjective emotion of the user is analyzed, the subjective preference of the user is better expressed, the explicit and implicit couplingrelation of the user / project characteristics is fused, and more accurate personalized recommendation is provided for the user. Meanwhile, the convolutional neural network is adopted, so that interaction between learning features at a deeper level is facilitated.
Owner:LIAONING TECHNICAL UNIVERSITY
Method for determining recommended information and related device
PendingCN112784151APrecise personalized recommendationOvercoming the problem of low precisionDigital data information retrievalMachine learningData miningData science
The invention discloses a method for determining recommended information and a related device. The method comprises the following steps: querying a target input method portrait, at least comprising a first tag of a target input method, of a target user; searching a first target information flow label corresponding to the first label of the target input method through a corresponding relation between an input method label system and an information flow label system; and based on the first target information flow label and the multiple pieces of candidate recommendation information, determining target recommendation information from the multiple pieces of candidate recommendation information by using an information click probability prediction model. The target input method label of the target user can be converted into the target information flow label representing the target information flow portrait of the target user by utilizing the corresponding relationship between the input method label system and the information flow label system. The invention solves the problem that the accuracy of recommended information is low due to the fact that a target user who does not have any click behavior on information in an information flow product cannot obtain an information flow portrait.
Owner:BEIJING SOGOU TECHNOLOGY DEVELOPMENT CO LTD
Display method and device for inputting associative words, storage medium and electronic equipment
PendingCN109491516AImprove experiencePrecise personalized recommendationInput/output processes for data processingPersonalizationSearch words
The embodiment of the invention discloses a display method and device for inputting association words, a storage medium and electronic equipment. The method comprises the steps that historical behavior data of a predetermined user are acquired; determining interest search words of a predetermined user according to the historical behavior data; searching interest search words matched with the received input words in all interest search words; and displaying the matched interest search word in the input association word list. According to the embodiment of the invention, the predetermined historical behavior data is acquired, the interest search term of the predetermined user is determined by combining the historical behavior data, and the interest search term matched with the input term isdisplayed in the input association word list; each user has the interest point of the user, through the embodiment of the invention, accurate personalized recommendation of thousands of people and thousands of faces can be realized, and the user experience is better.
Owner:BEIJING BYTEDANCE NETWORK TECH CO LTD
Financial management recommendation method, device and equipment based on behavior data
InactiveCN110598120AHigh precisionImprove conversion rateFinanceMulti-dimensional databasesClick-through rateData mining
The embodiment of the invention discloses a financial management recommendation method, device and equipment based on behavior data, and the method comprises the following steps: obtaining multi-dimensional attribute information and historical behavior data, wherein the multi-dimensional attribute information comprises financial management product multi-dimensional attribute information and corresponding user multi-dimensional attribute information; preprocessing the multi-dimensional attribute information and the historical behavior data, wherein the preprocessing comprises one or more of screening, clearness, missing value processing and singular value processing; inputting the preprocessed multi-dimensional attribute information into the constructed reinforcement learning model networkfor training to obtain recommended knowledge; and recommending the financing product to the target user according to the recommendation knowledge. By adopting the financial management recommendation method and device, the historical browsing behavior sequence information of the user is captured by using the reinforcement learning model, so that the financial management recommendation result is more accurate, and the click rate and the purchase rate of the user are greatly improved.
Owner:SUNYARD SYST ENG CO LTD
Recommendation method and device, computer readable storage medium and electronic equipment
PendingCN112115370AHigh degree of personalizationPrecise personalized recommendationDigital data information retrievalSpecial data processing applicationsPersonalizationEngineering
The embodiment of the invention discloses a recommendation method and device, a computer readable storage medium and electronic equipment. The method comprises the following steps of: recalling materials for a first user by adopting a plurality of recall strategies to obtain a plurality of recall results; judging whether recommended material behavior expression information of the first user existsin the historical behavior data or not to obtain a judgment result; determining a plurality of weights of a plurality of recall strategies for the first user in a corresponding weight determination mode according to a judgment result; fusing the plurality of recall results by adopting the plurality of weights to obtain a fusion result; and performing material recommendation to the first user according to the fusion result. According to the embodiment of the invention, the method can improve the personalized degree of the recommendation result during material recommendation, so as to achieve the precise personalized recommendation of a user.
Owner:BEIKE TECH CO LTD
Information recommendation method and device
PendingCN112256956AAchieve sharingRealize personalized recommendationDigital data information retrievalSpecial data processing applicationsPersonalizationWeb service
The invention discloses an information recommendation method and device, is used for realizing unified personalized recommendation for users between an application program interface and a Web page, and relates to the technical field of the Internet. One specific embodiment of the method comprises the steps that an application program end locally creates Web service for communicating with a Web page in a browser, the Web page in the browser requests the local Web service through communication, obtains a user ID pre-stored in an application program and communicates with a recommendation servicemodule, and the recommendation service module is used for recommending the user ID to the application program end; a recommendation service module generates personalized information corresponding to the user according to the received user ID and returns the personalized information to the Web page for display. According to the embodiment of the invention, the consistency of personalized recommendation of the same equipment and different media can be realized in a user non-inductive manner.
Owner:北京一亩田新农网络科技有限公司
A method and device for determining target object information corresponding to a user
ActiveCN103955480BImprove experienceAchieve acquisitionSpecial data processing applicationsInformation repositoryPersonalization
The invention aims to provide a method and equipment for determining target object information corresponding to a user in a resource information database. Processing equipment performs match inquiring in the resource information database according to an index word of the user to obtain candidate target object information corresponding to the index word, retrieval application information corresponding to the candidate target object information is determined according to corresponding retrieval log information of the user under the index word, and the target object information corresponding to the user in the resource information database is determined according to one or more pieces of candidate target object information and the retrieval application information. Compared with the prior art, the method and the equipment have the advantages that the target object information is obtained in a specific resource range, the accuracy and completeness of the obtained target object information are improved, the target object information obtaining efficiency is improved, further services such as personalized recommendation are accurately performed for the user, and the user experience is improved.
Owner:BAIDU ONLINE NETWORK TECH (BEIJIBG) CO LTD
A personalized commodity recommendation method and system
ActiveCN108629665BPrecise personalized recommendationObvious superiorityBuying/selling/leasing transactionsPersonalizationCosine similarity
The present invention discloses a personalized product recommendation method and system. The method includes: obtaining the historical behavior data of multiple users within a preset time period, and obtaining the first training sample after sorting according to predetermined rules; obtaining the influence factor based on the cosine similarity method as The second training sample; using the first training sample and the second training sample as the training samples of the deep learning model to train to obtain the trained deep learning model; outputting a list of commodities that the user is interested in predicted by the model. The invention effectively utilizes the timing information of commodities in the user's historical behavior, so that the commodities in the historical behavior have different weight values according to the time sequence of their interactive behavior in the calculation of the recommendation system, and the commodity impact factor reflects the global characteristics of the commodity and The user's interest in the product can effectively increase the feature quantity obtained by the deep learning model, and effectively improve the personalized recommendation effect for cold-start users.
Owner:BEIJING UNIV OF POSTS & TELECOMM +1
A multimedia data processing method and device
ActiveCN106484777BAccurate representation of preference informationPrecise personalized recommendationDigital data information retrievalSpecial data processing applicationsData miningProcessing
Embodiments of the invention disclose a multimedia data processing method and device. The method comprises the following steps of generating a multimedia data operation behavior matrix according to operation behaviors of a history user group for more data in a preset multimedia database; computing concealed feature vectors respectively corresponding to the multimedia data and user feature vectors respectively corresponding to history users based on a sparse self-encoding neural network according to the multimedia data operation behavior matrix; and when a recommendation request corresponding to a target user is received and the history user group includes the target user, obtaining a plurality of multimedia data in personal operation behavior information of the target user and carrying out recommendation processing on the multimedia data in the personal operation behavior information according to the user feature vector corresponding to the target user and the concealed feature vectors respectively corresponding to the multimedia data in the personal operation behavior information. Through adoption of the method and the device, the recommended song can be guaranteed to be liked by the user, so that the recommendation effect is improved.
Owner:TENCENT TECH (SHENZHEN) CO LTD
An association rule recommendation method based on adaptive multi-minimum support
ActiveCN103700005BPrecise personalized recommendationReduce sparsityMarketingPersonalizationValue set
The invention discloses an association-rule recommending method based on self-adaptive multiple minimum supports. The method comprises the following steps of firstly, establishing a commodity-classifying hierarchical tree according to commodity classification, and classifying concrete commodities according to the classifying hierarchical tree; next respectively carrying out minimum-support threshold-value setting on each concrete commodity and the upper-layer class of a concrete-commodity layer, and then mining frequent item sets and generating rules by utilizing a multiple-minimum-support association-rule expanding algorithm on the basis of the support threshold-value setting, wherein the threshold-value setting relates to the influences of time factors, concrete-commodity price factors and concrete-commodity brand factors; finally generating recommendation for each user by adopting a TOP-N recommending method. When personalized recommendation is made for the user by the association-rule recommending method, the characteristics of different objects can be better embodied by considering the influences of many factors on the multiple-minimum-support threshold-value setting for the concrete commodities and the classes; meanwhile, a data-sparsity problem and a cold-starting problem in a recommending system are relieved, so that the personalized recommendation can be more accurately made for the user.
Owner:SHANGHAI ZHENKE BUSINESS CONSULTING CO LTD
A program recommendation method
ActiveCN103686382BLock accuratelyPrecise personalized recommendationSelective content distributionPersonalizationClick-through rate
The invention relates to a program recommendation method. The program recommendation method comprises the following steps that firstly, television programs are classified according to the types of the programs; current watching information of each user is collected at preset intervals and is used as a watching historical record of the corresponding user; accurate personalized recommendation is achieved through the social relation correlation based on the users and the content matching technology based on the historical records. By the adoption of the program recommendation method, the defects of the mode that recommendation is conducted through simple statistics of the program click rate completely based on individual interest and habit of watching the television programs are overcome, a television program provider can more accurately lock clients and improve the audience rating, and therefore accurate marketing can be achieved.
Owner:NANJING UNIV OF INFORMATION SCI & TECH
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