Abstract: A cloud scraping system using pre-scraped big data includes an information providing server which, when receiving a scraping request from a user terminal, provides the user terminal with response information to the received scraping request, and a big data storage which stores pre-scraped information, wherein when the scraping request is about static information, the information providing server acquires the response information using the pre-scraped information. According to the above cloud scraping system using pre-scraped big data, there is an advantage that it is possible to quickly respond to a scraping request from the user terminal afterwards by pre-scraping and storing static information in the big data storage. Additionally, it is possible to improve the scraping server operation efficiency by making a proper use of a single or multi-processing scraping server based on policy information of a scraping target external institution.

Abstract: A deposit and withdrawal service system using Automated Teller Machine (ATM) includes a communication module configured to receive a transaction request associated with a customer's asset managed by an institution from the ATM, and transmit a processing result received from the institution in response to the transaction request to the ATM, and a statement conversion module configured to convert the transaction request received from the ATM into aggregated details data that is independent from the ATM, and convert the processing result received from the institution into statement details data corresponding to the ATM having requested the transaction. The communication module is further configured to transmit the aggregated details data to the institution, receive the processing result from the institution, and transmit the processing result to the ATM as the statement details data.

Abstract: A cloud scraping system using pre-scraped big data includes an information providing server which, when receiving a scraping request from a user terminal, provides the user terminal with response information to the received scraping request, and a big data storage which stores pre-scraped information, wherein when the scraping request is about static information, the information providing server acquires the response information using the pre-scraped information. According to the above cloud scraping system using pre-scraped big data, there is an advantage that it is possible to quickly respond to a scraping request from the user terminal afterwards by pre-scraping and storing static information in the big data storage. Additionally, it is possible to improve the scraping server operation efficiency by making a proper use of a single or multi-processing scraping server based on policy information of a scraping target external institution.

Abstract: A cloud scraping system using pre-scraped big data includes an information providing server which, when receiving a scraping request from a user terminal, provides the user terminal with response information to the received scraping request, and a big data storage which stores pre-scraped information, wherein when the scraping request is about static information, the information providing server acquires the response information using the pre-scraped information. According to the above cloud scraping system using pre-scraped big data, there is an advantage that it is possible to quickly respond to a scraping request from the user terminal afterwards by pre-scraping and storing static information in the big data storage. Additionally, it is possible to improve the scraping server operation efficiency by making a proper use of a single or multi-processing scraping server based on policy information of a scraping target external institution.

Abstract: A cloud scraping system using pre-scraped big data includes an information providing server which, when receiving a scraping request from a user terminal, provides the user terminal with response information to the received scraping request, and a big data storage which stores pre-scraped information, wherein when the scraping request is about static information, the information providing server acquires the response information using the pre-scraped information. According to the above cloud scraping system using pre-scraped big data, there is an advantage that it is possible to quickly respond to a scraping request from the user terminal afterwards by pre-scraping and storing static information in the big data storage. Additionally, it is possible to improve the scraping server operation efficiency by making a proper use of a single or multi-processing scraping server based on policy information of a scraping target external institution.

Abstract: A cloud scraping system using pre-scraped big data includes an information providing server which, when receiving a scraping request from a user terminal, provides the user terminal with response information to the received scraping request, and a big data storage which stores pre-scraped information, wherein when the scraping request is about static information, the information providing server acquires the response information using the pre-scraped information. According to the above cloud scraping system using pre-scraped big data, there is an advantage that it is possible to quickly respond to a scraping request from the user terminal afterwards by pre-scraping and storing static information in the big data storage. Additionally, it is possible to improve the scraping server operation efficiency by making a proper use of a single or multi-processing scraping server based on policy information of a scraping target external institution.

Abstract: A data scraping system includes: a management module having a service program that calls inquiry or execution requiring scraping to receive user information for scraping and allocate user information and a task using an internal scheduling algorithm; and a scraping module connected to a plurality of different institutions, allowing communication, based on the user information and the task allocated by the management module, to scrape data corresponding to the called inquiry or execution from the plurality of institutions. The scraping module includes a meta database to designate a data item to be scraped, and is configured to extract data to scrape based on the meta database from a data set provided by the institution. According to the data scraping system, it is possible to enable data scraping in various platforms such as mobile computing devices, and collect multiple scraping information in one device without constraints of a security module.

Abstract: A data scraping system includes: a management module having a service program that calls inquiry or execution requiring scraping to receive user information for scraping and allocate user information and a task using an internal scheduling algorithm; and a scraping module connected to a plurality of different institutions, allowing communication, based on the user information and the task allocated by the management module, to scrape data corresponding to the called inquiry or execution from the plurality of institutions. The scraping module includes a meta database to designate a data item to be scraped, and is configured to extract data to scrape based on the meta database from a data set provided by the institution. According to the data scraping system, it is possible to enable data scraping in various platforms such as mobile computing devices, and collect multiple scraping information in one device without constraints of a security module.

Abstract: A cloud scraping system using pre-scraped big data includes an information providing server which, when receiving a scraping request from a user terminal, provides the user terminal with response information to the received scraping request, and a big data storage which stores pre-scraped information, wherein when the scraping request is about static information, the information providing server acquires the response information using the pre-scraped information. According to the above cloud scraping system using pre-scraped big data, there is an advantage that it is possible to quickly respond to a scraping request from the user terminal afterwards by pre-scraping and storing static information in the big data storage. Additionally, it is possible to improve the scraping server operation efficiency by making a proper use of a single or multi-processing scraping server based on policy information of a scraping target external institution.