14 results about "Market activity" patented technology

The invention discloses a marketing management method and system based on big data analysis, and relates to the technical field of marketing management, and the method comprises the steps: analyzing the behavior data of a marketing target user, and constructing a marketing target user portrait; outputting a marketing strategy of the marketing target user and the associated user through the behavior record of the associated user in combination with the portrayal analysis of the marketing target user; adjusting marketing strategies of the marketing target user and the associated user based on the market data; the adjusted marketing strategy is applied to market activities, and the marketing process and the market risk condition are monitored in real time; marketing achievements of all stages are obtained based on real-time monitoring, the marketing achievements are analyzed, a marketing change trend is recognized, a marketing strategy optimization mechanism is triggered based on the marketing change trend, and a marketing strategy is adjusted and optimized. Accurate marketing, strategy dynamic adjustment and resource optimal configuration are realized, and the marketing efficiency and effect are remarkably improved.

A method for using an artificial intelligence (AI) technique to forecast market activities by specific parties with respect to derivatives and other specific types of financial instruments is provided. The method includes: retrieving first information that relates to at least one form that corresponds to a government filing; generating, based on the first information, a first knowledge graph that relates to an entity, such as a commercial concern; retrieving second information that relates to historical actions performed by at least one person that is associated with the entity; and forecasting, based on the first knowledge graph and the second information, at least one proposed future transaction to be executed by the person with respect to the first entity. The forecasting is based on an application of an AI algorithm to the information retrieved from the government filing(s).

A multi-level, multi-system, pan-center cooperation platform system and method based on blockchain. The system includes multiple hierarchical nodes forming a flat structure. When demand is allocated, nodes of the demand type can publish demand request messages in the system. Nodes of the supply type match the information of the demanded product carried in the demand request message with the information of the supplier's product stored in the node. When multiple suppliers are matched, the multiple suppliers are processed through a game algorithm to obtain allocation results. The nodes of the demand type select the appropriate allocation results, completing the product allocation process based on blockchain-based collaborative competition. The system is established based on blockchain, and anti-monopoly is realized at the macro level. Micro rules are determined for different products between the bottom suppliers, thereby realizing macro and micro regulation, promoting the activity and fairness of the market, improving the turnover rate of resources, reducing the cost of collaboration, and improving the interests and enthusiasm of all market participants at all levels.

The invention discloses an AI material generation acceleration method for e-commerce propaganda, and relates to the technical field of e-commerce propaganda, and the method comprises the following steps: at the beginning stage of video editing, firstly processing a video to be edited through a preset editing period by an AI technology, and guaranteeing that the initial stage of video editing reaches a quality standard; according to the method, the video complexity is intelligently evaluated, the editing time is dynamically adjusted, the editing period is shortened, the manufacturing process is accelerated, the production efficiency is improved, it is ensured that an e-commerce platform responds to market activities in time under the high-concurrency requirement, and key promotion opportunities are prevented from being missed. And for a video with a complex concept, a preset editing period is continuously adopted, and deep analysis of emotion fluctuation, visual contrast and other characteristics is combined with a long and short-term memory network, so that video quality maximization is ensured, logicality, fluency and visual effect are accurately adjusted and optimized, and user experience, brand image and conversion rate are improved.

We provide the system. [Solution] A means of collecting and storing users' payment history in a database, A method for analyzing payment history collected using machine learning algorithms and extracting user purchasing patterns, A means for generating product recommendations based on user-specific purchasing patterns, A means of collecting the latest market activity information and making the best possible proposals to users, A means of analyzing natural language input from users and providing appropriate information, A means of selecting and notifying market activity information when arriving at a specific facility using location information, A system that includes this.

The invention discloses a catering member intelligent marketing method and system based on a large model, and relates to the technical field of large model and business data cross analysis, and the method comprises the steps: firstly interpreting a commercial tenant demand, if the commercial tenant demand is a query demand, recognizing the query demand through the large model, organizing a language, and returning a query result; if yes, whether the commercial tenants need to be grouped and selected is determined, and if yes, designated grouping information is read, and then designated group selection operation is performed through interaction with the commercial tenants; if not, all information of a default grouping method is read for intelligent group selection; and marketing suggestions are returned according to the merchant marketing demands and the user grouping and selecting information. According to the method, multi-source data are integrated, semantic understanding, behavior prediction and dynamic optimization capabilities of a large model are utilized, and after marketing activity feasibility auditing and improvement are performed in combination with manual work, a system guides a merchant to execute a corresponding marketing activity, so that a more personalized and accurate marketing strategy can be realized, and the user experience and the merchant operation efficiency are improved.

The invention relates to the technical field of depth data processing, in particular to a data evaluation method, a data evaluation model, a data evaluation system and a computer readable storage medium. A plurality of market factor combinations are selected to calculate an industry market index representing market activeness, and the industry market index and historical price data are introduced to be input into a time sequence analysis model for price prediction; different pricing weights are given on the basis of different buyer identities to realize differential pricing, so that an evaluation result which is more in line with the expectation of the buyer is generated, and the transaction matching accuracy is improved. The invention aims to solve the problem of how to introduce market factors and differentiated pricing weights to carry out data value evaluation.

The invention provides a fresh food demand prediction method and system based on a cloud warehouse system, and the method comprises the steps: firstly obtaining multi-source demand time sequence data, including historical order fluctuation, environment perception monitoring and market activity association sequences, in a preset period of a target region, and then carrying out the time sequence, space and event feature coding of each sequence, the method comprises the steps of generating corresponding features, inputting the corresponding features into a regional warehouse group feature update network to obtain regional warehouse group features with dynamic adaptive capacity, generating predicted demand features containing multi-time granularity fresh food category demand quantity distribution through a decoder of a demand prediction model, and finally dynamically adjusting inventory configuration parameters of a cloud warehouse system according to the features. And the deviation rate of the fresh food reserve of the regional warehouse group and the predicted demand quantity is lower than a preset value, so that the fresh food demand can be comprehensively and accurately predicted, the cloud warehouse inventory configuration is optimized, and the operation efficiency is improved.

The invention relates to an activity cost and target prediction method, and relates to the technical field of marketing and data analysis, and the method comprises the following steps: collecting and sorting historical activity data, generating a user portrait, obtaining the current sales condition in real time, and comprehensively analyzing key factors influencing the activity effect. Specific sales targets and key performance indicators are set, multiple activity schemes are designed, and real-time monitoring and feedback are carried out in the implementation process. According to the method, the historical activity data, the user portrait, the current sales condition and the sales target are integrated, and the corresponding market activity scheme is formulated by using a big data technology, so that the accuracy and effect of market activities can be improved, resource allocation is optimized, the cost is reduced, and the method has a wide application prospect.

The invention discloses a dynamic data access authorization method, system and device based on market activeness and a medium, mainly relates to the technical field of access authorization, and is used for solving the problem of low efficiency of manual maintenance and updating of a data access control strategy in the existing scheme. Data potential safety hazards exist, and the data market value is not activated. Comprising the following steps: loading an authorized data directory to a data market operation platform, and displaying the authorized data directory through the data market operation platform; the data demander downloads authorization data in the sub-authorization data catalog from the data market operation platform according to the dynamic data catalog token; the data market operation platform generates market activeness of each piece of authorization data; obtaining a portrait analysis result of the demand user; determining a recommended data directory of each data demander according to the portrait analysis result and preset user description of the data demander; wherein the recommended data catalog belongs to the authorized data catalog.

The invention relates to the technical field of intelligent Internet of Things, and particularly provides a market supervision and inspection method and device, and the method comprises the following steps: S1, an Internet of Things equipment deployment module collects market activity data in real time; s2, the data acquisition and transmission module transmits data to a data center by using a wireless network technology; s3, the data analysis and early warning module processes and analyzes the collected data; and S4, a supervision task generation and distribution module automatically generates a specific supervision task and distributes the task to a corresponding supervisor. S5, an inspection execution and feedback module performs field inspection according to the distributed tasks; and S6, performing system maintenance and upgrading, and improving functions and performance of the system. Compared with the prior art, the requirements of manual operation and intervention are greatly reduced, and the market supervision efficiency is remarkably improved.

The invention relates to a distributed energy resource regulation and control method and system considering market demands, and the method comprises the following steps: carrying out the clustering analysis of the electrical characteristic data, geographic position data and available time data of each distributed energy resource, and obtaining a distributed energy resource characteristic classification result; based on a distributed energy resource characteristic classification result, constructing a distributed energy resource aggregator clearing model; solving the distributed energy resource aggregator clearing model through an optimization algorithm to obtain a distributed energy resource combination participating in the market transaction; and calculating the final payment price of the user and the actual contribution degree of the distributed energy resources in the electricity market based on the optimal distributed energy resource combination participating in the market transaction. A market transaction combination is determined through an optimization algorithm, the capability of dealing with market changes is enhanced, all parties are promoted to actively participate in market activities through a pricing mechanism integrating three aspects of marginal cost, time contribution and flexible contribution, and a fair competition environment is ensured.