30results about How to "Intelligent Recommendation" patented technology

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.

The invention relates to the technical field of recommendation systems, in particular to a personalized intelligent clothes matching recommendation method in combination with a knowledge graph, which comprises the following steps: acquiring clothes commodity information and user clothing interaction information of an e-commerce platform, and constructing the knowledge graph; modeling the knowledge graph, and learning each entity and relationship in the knowledge graph to obtain an entity vector and a relationship vector; combining the entity vector and the relationship vector with a hybrid recommendation system, and performing score prediction on the single clothing to obtain a clothes single recommendation result; and calculating a matching index of every two clothes single items, automatically matching the two clothes single items with high matching indexes, performing score prediction, and performing a final TOP-N suit recommendation result according to scores. Online clothes suit recommendation is more intelligent.

The invention relates to a satellite network safety analysis method, a device, a system and a storage medium. The method comprises the steps of obtaining equipment safety data of a satellite network and completing model construction of a satellite network safety ontology; uniformly processing the equipment safety data according to the satellite network safety equipment four-level model, and respectively forming a satellite network safety level model and a satellite network safety knowledge model; abstracting entity names, attributes and interrelationships from the satellite network safety hierarchy model and the satellite network safety knowledge model, and formally expressing the entity names, attributes and interrelationships as dynamic triples by adopting a set description language to obtain a dynamic graph model; carrying out knowledge reasoning and graph dynamics analysis based on an OWL + SWRL language, and completing auxiliary construction of the satellite network equipment safety knowledge graph; and obtaining a safety problem query statement, and performing knowledge reasoning and query analysis through the constructed knowledge graph to obtain safety weak link information of the satellite network. The analysis efficiency of the satellite network safety weak link is greatly improved.

The invention relates to the technical field of data analysis and discloses a course recommendation method, device and equipment and a computer readable storage medium. The method comprises the stepsthat according to personal information of a to-be-selected person, the similarity between the to-be-selected person and all course selection completion users is calculated, a calculation result is obtained, and whether a target course selection completion user similar to the to-be-selected person exists or not is detected according to the calculation result; and if the target course selection completion user similar to the to-be-selected person does not exist, the personal information of the to-be-selected person is input into a prediction model to obtain a course recommendation result for the to-be-selected person. According to the invention, the course can be automatically recommended to the user according to the personal information of the user, so that the course recommendation is more intelligent.

The embodiment of the invention provides a textile raw material recommendation method and device, a processor and a storage medium. The method comprises the steps of obtaining behavior data of a user; according to the behavior data, determining the interest degree of the user for the textile raw material commodity in each dimension and the user similarity between the users; determining a first recommendation candidate set for the user according to the interest degree; determining the raw material similarity between the raw material commodities; determining a second recommendation candidate set of the users according to the user similarity and the raw material similarity; inputting at least one of the behavior data of the user, the raw material features of the textile raw materials and the context information into a prediction model to determine a third recommendation candidate set of the user; determining a final recommendation set of the user according to the first recommendation candidate set, the second recommendation candidate set and the third recommendation candidate set; and determining the raw material commodities included in the final recommendation set as recommended raw material commodities for the user.

The embodiment of the invention relates to the field of intelligent equipment, and discloses a learning content recommendation method and a family education device. The method comprises the followingsteps: acquiring a large number of voice data samples and regional information samples of users in different regions; training by taking the voice data sample as training data and the regional information sample as a training result to obtain a regional recognition model; acquiring voice data of the target user according to the received voice control instruction of the target user; inputting the voice data into a region recognition model to obtain region information of a target user; and recommending the learning corresponding to the regional information to the target user. By implementing theembodiment of the invention, different learning contents can be recommended to users in different regions based on voice recognition, and the recommendation mode of the learning contents can be simpler and more intelligent.

The invention discloses a risk assessment method and server for optimized combination, and the method comprises the steps: forming a transaction data set through the transaction information of one or more than one securities in a securities market, and fitting an assessment coefficient beta i and an assessment factor Xi through the transaction data set; and then loading the evaluation coefficient [beta]i and the evaluation factor Xi into a regression equation, so that the yield rate of the target security is solved, and investment funds are allocated according to the yield rate to obtain the maximum income.

The invention provides a sick and wounded transfer route recommendation method and system based on artificial intelligence, and the method comprises the steps: collecting and obtaining first sick and wounded group information which comprises sick and wounded position information and sick and wounded condition information; acquiring first transfer position information; according to the position information of the sick and wounded and the first transfer position information, preliminarily planning to obtain multiple pieces of route information; setting a multi-dimensional optimization condition, wherein the multi-dimensional optimization condition comprises sick and wounded condition information and transfer time information; according to a multi-dimensional optimization condition, performing optimization in the multiple pieces of route information to obtain optimal route information; and transferring the sick and wounded by adopting the optimal route information. According to the method and the device, the technical problems of inaccuracy, non-intelligence and reduction of the sick and wounded transferring efficiency in a sick and wounded transferring route determination method in the prior art are solved.