Abstract: Disclosed are a method for providing a compressed gig service and a device therefor, the method comprising the steps of: obtaining compressed gig service information including service content, service time, and service area; predicting an order amount for the compressed gig service information; determining the price for the compressed gig service information on the basis of the compressed gig service information and the order amount; generating a gig service offer including the compressed gig service information and a gig service price; and transmitting the gig service offer to at least one gig service requester terminal.

Abstract: Disclosed are a method and device for job scheduling for a gig worker, the device comprising: a data obtaining unit obtaining gig service completion data and gig service request data generated in a preset time section or a preset space section; and a prediction unit predicting a gig service load rate, a gig service rate, the number of gig workers to provide a gig service, and the number of gig service requests to be generated in a particular time section or a particular space section on the basis of at least one piece of the gig service completion data and the gig service request data, wherein the prediction unit, on the basis of at least one piece of the gig service completion data, further predicts the number of gig services that a gig worker is capable of performing in the particular time section or the particular space section; and further predicts the income of each gig worker on the basis of the gig service rate and the number of gig services that the gig worker is capable of performing.

Abstract: Disclosed are a system and method for predicting a gig service in accordance with spatio-temporal characteristics, the system comprising: a data acquisition unit for acquiring gig service completion data and gig service request data generated in a preset time interval or a preset space interval; a prediction unit for generating prediction data associated with the number of gig service requests to be generated in a specific time interval or a specific space interval and the number of gig workers who will provide the gig service, by means of the gig service request data and/or the gig service completion data; a load ratio determination unit for determining a service load ratio of number of gig workers to number of gig service requests in the specific time interval or the specific space interval, by means of the generated request data; and a load ratio providing unit transmitting the service load ratio to an external terminal.

Abstract: Disclosed are a business opportunity information recommendation server and a method therefor, the server comprising: a data acquisition unit for acquiring, on the basis of an external input, lead data, lead buyer data, and lead seller data, which are pieces of product- or service-related business opportunity information about a customer; a learning unit for generating, on the basis of the lead data, the lead buyer data, and the lead seller data, a learning model by being trained for deep learning; a prediction unit for predicting, on the basis of the learning model, the degree of association between a lead buyer and a lead, the degree indicating the purchase possibility of the predetermined lead buyer for each piece of lead data being sold; and a recommendation unit for generating a first lead recommendation list, which includes at least one piece of lead data being sold, arranged by the degree of association between the lead buyer and the lead with respect to the predetermined lead buyer.

Abstract: Disclosed are a selling system using a correlation analysis network, and a method therefor, the system comprising: a collection unit for collecting seller data, product data, and purchaser data; a node acquisition unit for acquiring a plurality of graph nodes including a seller node, a product node, and a purchaser node; a feature acquisition unit for acquiring at least one piece of feature information indicating the attribute value of each of the plurality of graph nodes on the basis of the seller data, the product data, and the purchaser data; an edge acquisition unit for acquiring, on the basis of the at least one piece of feature information, edge information indicating the correlation between the plurality of graph nodes; a graph structure acquisition unit for acquiring a graph structure including the plurality of graph nodes, the at least one piece of feature information about each of the plurality of graph nodes, and the edge information; a learning unit for learning the graph structure by using a grap

Abstract: Provided is a platform operator device supporting an issuance of multi-assets-backed security tokens on a blockchain network. The platform operator device comprises memory, a processor, a display unit, and a communication unit.

Abstract: Disclosed are a business opportunity information sales system and a method thereof, the system comprising: a lead sales application including a registration unit for temporarily registering a lead, which is product- or service-related business opportunity information for a customer, on the basis of an external input from a lead seller, and a sales unit for receiving as an input of a purchase request for a purchase lead among at least one predetermined lead provided from a lead management server, on the basis of an external input from a predetermined lead purchaser; and the lead management server including a registration unit for registering the lead obtained from the lead sales application in a database, and a sales unit for providing the least one predetermined lead in the database to the lead sales application so as to be output to the predetermined lead purchaser.

Abstract: Disclosed are a system for providing stable salary and a method therefor, the system comprising: an input unit that receives, as an input, a salary payment date having a predetermined cycle, on the basis of an external input; a learning data acquisition unit that acquires learning data including worker information, work history information, and salary history information, on the basis of the external input; a future credit period acquisition unit that determines a future credit period on the basis of at least one of the pieces of learning data; a future income prediction unit that performs machine learning by using at least one of the pieces of learning data, and predicts future income for the future credit period; and a virtual salary determination unit that, when the amount of a worker's salary is less than the target amount of salary at a specific point in time of payment of salary, determines virtual salary in which the insufficient amount of salary in the target amount of salary has been covered on the b