40results about How to "Realize accurate recommendation" patented technology

The embodiment of the disclosure provides a route planning method based on traffic rules. The route planning method comprises the steps: acquiring a target road network map; generating a road networktopological graph including a plurality of nodes expressing road segments according to the target road network map; acquiring preset traffic rule information corresponding to each node; judging whether every two nodes in the road network topological graph pass or not according to the preset traffic rule information; updating the road network topological graph to generate a target road network topological graph according to a judgment result that whether every two nodes pass or not; and performing route planning based on the target road network topological graph. Correspondingly, the embodimentof the invention further provides a route planning device based on the traffic rules, computer equipment and a computer readable storage medium. According to the embodiment of the invention, the traffic rules are applied to route planning, so that accurate route recommendation is realized; the route with relatively low passing cost can be recommended to the user; and the data processing efficiency can be effectively improved.

The invention provides a user tag extension treatment method. The method includes the steps of obtaining a user tag and candidate expanded tags, conducting mutual information calculation between the user tag and the candidate expanded tags to obtain the correlation of the candidate expanded tags relative to the user tag, screening out extension tags in the candidate expanded tags according to the correlation to obtain the extension tags correlated to the user tag, wherein an extension relation between the user tag and the correlated extension legs is formed. In addition, the invention further provides a user tag extension treatment device matched with the method and a text recommendation method and device. By means of the user tag extension treatment method and device, the user tag extension precision can be improved; by means of the text recommendation method and device, the text precise recommendation can be realized on the basis of user tag precise extension.

The invention discloses a product recommendation method and system combining paired optimization and matrix decomposition. The method comprises the steps of obtaining a scoring matrix of a user to a product and a social relation matrix between the users; clustering the products according to the scoring matrix of the users to the products, and dividing the products into a plurality of clusters; mapping the scoring matrix of the user to the product and the social relation matrix between the users into a weighted adjacency matrix; defining a user-product bipartite graph, and filling the weightedadjacent matrix on the user-product bipartite graph by using a random walk algorithm to obtain a probability matrix; establishing an objective function based on the paired optimization pairwise basedon the divided clusters of the products; and performing matrix decomposition on the probability matrix based on the objective function, and obtaining a decomposed matrix and a product recommendation list by taking the minimum objective function value as an objective.

The invention discloses an IoT edge equipment trust evaluation method. A time window method is employed to obtain a predicted trust value in a current cycle according to trust values of equipment in past time cycles; trust has time correlation, and thus the predicted trust value delineates a possible range of a current trust value to a certain extent; a difference value of a received actual trustvalue and the predicted trust value is compared with an error threshold, and whether the trust value of interaction can be trusted is judged; if not, the trust value is corrected through implementinga penalty system, then aggregation calculation of feedback trust is carried out after correction, and a more reliable overall trust value can be obtained; and malicious evaluation caused by maliciousbehaviors such as false feedback, malicious attacks and collusion cheating is avoided, and reliability of overall trust and security of a system are improved. The invention also discloses an IoT edgeequipment trust evaluation device, an edge proxy server and an IoT edge equipment trust evaluation system, which have the above advantages.

The embodiment of the invention discloses a service object recommendation method and device and electronic equipment. The service object recommendation method includes: acquiring anchor attribute information of a live-streaming room and all pieces of service object attribute information; determining a target service object on the basis of the anchor attribute information and all the pieces of service object attribute information; and displaying the target service object in the live-streaming room. Through the embodiment of the invention, the service object matching a video anchor can be selected from a service object library for the video anchor, the service object better meets needs of the video anchor, and precise recommendation of the service object is realized.

The invention relates to a keyword extraction method and device and a storage medium, and the method comprises the steps: receiving an original document, extracting a plurality of candidate phrases from the original document, and enabling the extracted candidate phrases to form a candidate set; obtaining the association degree between each candidate phrase in the candidate set and the original document; obtaining divergence of each candidate phrase in the candidate set; and selecting at least one candidate phrase from the candidate set as a key phrase based on the correlation degree and the divergence degree, and forming a key phrase set of the original document based on the selected at least one key phrase. Thus, the candidate phrases with the high association degree with the original document can be selected from the candidate set to serve as the key phrases, the similarity between the extracted key phrases and the original document is high, and the accuracy of extracting the key phrases is improved; the phrases with high divergence can be selected from the candidate set to serve as the key phrases, so that the difference degree between the extracted key phrases and the key phrases selected to the key phrase set is high, and the diversity of the key phrases is improved.

The invention discloses a method for multimedia recommendation on the basis of data grading. The method comprises the following steps of receiving a selection instruction of a user on the category, and obtaining index data of multimedia in the selected category; classifying the index data of the multimedia according to sites, and performing statistics to obtain the index data of the multimedia of each site; obtaining the grading of the multimedia in each site through calculation according to the index data of the multimedia of each site; performing unified sequencing on the multimedia of different sites according to the grading result in accordance with the grading values, and recommending the multimedia to the user according to the sequencing. The invention also discloses a system for multimedia recommendation on the basis of data grading. The method and the system for multimedia recommendation on the basis of data grading have the advantages that the grading of the multimedia is obtained through calculation through the index data of the multimedia in one site, so that the multimedia of different sites can be sequenced according to the grading; the precise recommendation of the multimedia is finally realized; further, the experience degree of the user is improved.

The invention provides a business recommendation method and a business recommendation device. The business recommendation method comprises the following steps that: obtaining historical business ordering feature information; according to the historical business ordering feature information, determining recommended target feature information; and according to the recommended target feature information, recommending the business to a recommendation target corresponding to the recommended target feature information according to the recommended target feature information. By use of the business recommendation method and the business recommendation device, accurate business recommendation is realized, and the accuracy of user experience and business recommendation is improved.

The invention discloses a film and television resource personalized recommendation method in a social network environment, and belongs to the technical field of data analysis and pushing. The method includes the following steps of S1, online comment obtaining and preprocessing, S2, online comment emotion value calculation, S3, film watching decision criterion and weight determination, and S4, film and television resource sorting: a comprehensive foreground value of a film xi is obtained by combining a probability language decision matrix, a value function and a weight function, wherein the larger the comprehensive foreground value is, the more worthy of recommendation is achieved, and the higher the sorting is. According to the method, the influence of irrational factors such as psychological behaviors of film viewers on decision making of the film viewers is fully considered while objective factors are considered, so that film and television resource recommendation is more practical and accurate.

The invention discloses a recommended item determination method and device, electronic equipment and a storage medium and relates to the technical field of computers. A specific embodiment of the method comprises the following steps of acquiring article information of articles browsed by each user in a preset time period, wherein the article information comprises attributes of the browsed articles and a browsing sequence corresponding to the browsed articles; according to the browsing sequence corresponding to the browsed items, the feature vector of each browsed item being calculated, and the feature vector representing the incidence relation between the browsed items; calculating similarity between each browsed article and the target article according to the feature vector of each browsed article; and according to the similarity and the attribute of the browsed article, determining a recommended article corresponding to the target article. According to the method, problems that accuracy of a mode of determining recommended articles based on categories is low, and accurate recommendation of the articles cannot be realized can be solved.

The invention discloses an activity information processing method, device and equipment, relates to the technical field of information processing, and aims to accurately control activity resources without configuring activity information by a service party and improve the recommendation effect of the activity information. The method comprises the steps: obtaining first activity data generated whena service party delivers activity information; based on the first activity data, selecting an activity information template suitable for being released by a service party for pushing; acquiring second activity data generated by updating the activity information template by the service party; determining a verification result of an activity information template based on the first activity data andthe second activity data; and sending a verification result of the activity information template.

The invention relates to a data recommendation method and device, a server and a storage medium, and belongs to the technical field of computers. The method comprises the steps of obtaining target data features corresponding to to-be-recommended target multimedia data, calling a feature conversion model, performing feature transformation processing on the target data features to obtain transformed predicted operation features, determining the matching degree of each user and the target multimedia data according to user features corresponding to multiple users and the predicted operation features, and recommending the target multimedia data according to the matching degree of each user and the target multimedia data. And selecting at least one target user from the plurality of users according to the matching degrees corresponding to the plurality of users, and recommending the target multimedia data to the at least one target user. According to the method, the predicted operation characteristics of the multimedia data are used for representing the operation possibly executed by the user on the multimedia data, the user matched with the multimedia data is determined, and the multimedia data are subsequently recommended to the matched user, so that accurate recommendation of the multimedia data is realized, the accuracy of data recommendation is ensured, and cold start of the multimedia data is realized.

The invention discloses a medical system labor dispatch management system and a working method thereof. The medical system labor dispatch management system comprises a labor supplier module, a labor demand entry module, a management settlement module and an offer invitation module. The offer invitation module comprises a selection pushing assembly, a confirmation feedback assembly, a contract pushing assembly, a user side and a worker offer side. The contract pushing assembly comprises a user interface and an offer interface, the user interface is connected with the user side, the offer interface is connected with the worker offer side. The user interface and the offer interface are respectively provided with a corresponding Tag marking assembly, and each Tag marking assembly comprises a timing gear returning function. The system has the advantages that when labor purchasing is carried out on line and an employment relationship of labor dispatching is reached, temporary employment relationship marking can be carried out on the corresponding labor supplier and the service purchaser through the Tag marking assembly, so that the labor supplier can be conveniently managed by a worker, and salaries and persons in charge can be conveniently issued.

The invention relates to an article recommendation method and device, a meta-network processing method and device, a storage medium and equipment. The article recommendation method comprises the stepsof obtaining attribute information of an article and an object identifier of an article interaction object; performing feature extraction on the attribute information through a meta-stretching network to obtain a stretching vector; performing feature extraction on the object identifier through a meta-offset network to obtain an offset vector; performing feature intersection on the vectorized article identifier of the article and the stretching vector, and fusing the obtained intersection feature vector with the offset vector to obtain a fused feature vector; determining a recommendation probability based on the fusion feature vector, the vectorized attribute information and vectorized object information of the target object; and recommending the article to the target object when the recommendation probability meets a recommendation condition. By adopting the method, the accuracy of article recommendation can be improved, so that the effect of accurate recommendation is achieved.