Outbound scene data query method and device, computer equipment and storage medium

Abstract

The embodiment of the invention discloses an outbound scene data query method and device, computer equipment and a storage medium. The method comprises the following steps: constructing various call-out scene real-time query data to obtain personalized data; dialogue data of the outbound scene is acquired; performing question discrimination processing on the dialogue data to obtain a personalized query question; analyzing the personalized query question into a query SQL (Structured Query Language) statement; according to the query SQL statement, querying corresponding contents from the personalized data to form a query result; judging whether the query result is a data response-free result or not; and if not, packaging the data corresponding to the query result, and outputting the packaged data. By implementing the method provided by the embodiment of the invention, the real-time data query capability of the outbound system can be realized, and an accurate response result of a personalized data query requirement is provided.

Description

technical field [0001] The present invention relates to a computer, and more specifically refers to an outcall scene data query method, device, computer equipment and storage medium. Background technique [0002] In banking and financial intelligent outbound telemarketing scenarios, such as: credit card promotion or credit limit increase, repayment reminders and many other outbound call scenarios, users often encounter personalized data query needs, such as "Help me check last month's How much is the bill?" or "How much is my current balance?" or "In the last 2 years, check how many times I have overdue." For manual customer service, it is generally possible to give correct feedback according to the needs of users. Most of the outbound call systems are difficult to solve or guide the problem of part of speech correctly, which makes it impossible to meet the user's information consultation expectations and greatly reduces the effect of the entire outbound call. [0003] Ther...

AI Technical Summary

Problems solved by technology

[0002] In banking and financial intelligent outbound telemarketing scenarios, such as: credit card promotion or credit limit increase, repayment reminders and many other outbound call scenarios, users often encounter personalized data query needs, such as "Help me check last month's How much is the bill?" or "How much is my current balance?" or "In the last 2 years, check how many times I have overdue." For manual customer service, it is generally possible to give correct feedback according to the needs of users. Most of the outbound call systems are difficult to solve or guide the problem of part of speech correctly, which makes it impossible to meet the user's information consultation expectations and greatly reduces the effect of the entire outbound call

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