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Order formation prediction method and device in customer service dialogue process and electronic equipment

A prediction method and single prediction technology, applied in the computer field, can solve problems such as unfavorable adjustment of dialogue behavior, the prediction rate of not having multiple sentences, and the impact of single results.

Active Publication Date: 2022-06-03
CHENGDU XIAODUO TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the difference in ability between customer service personnel, for the same buyer, the final order result is affected by the ability of customer service personnel
By collecting and summarizing the order rate data, the sales experience of customer service personnel can be enriched; the existing technology needs to accumulate multiple sets of data before it can be given a posteriori, and it cannot be given in the dialogue chat The real-time prediction of the order completion rate is not conducive to the real-time adjustment of the dialogue behavior of the customer service staff
Traditionally, a single sentence is encoded as a sentence vector, and then other semantic recognition, emotion recognition and other operations are performed, and multiple sentences in a dialogue are not used together to predict the single rate

Method used

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  • Order formation prediction method and device in customer service dialogue process and electronic equipment
  • Order formation prediction method and device in customer service dialogue process and electronic equipment
  • Order formation prediction method and device in customer service dialogue process and electronic equipment

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

As an example, as attached figure 1 As shown, in order to solve the above-mentioned technical problems, the present embodiment provides a method for predicting order formation in a customer service dialogue process, including the following steps:

Get historical conversation data;

Query the order log according to the historical dialogue data, and determine the buyer's order log corresponding to the historical dialogue data within the set time range;

According to the buyer's order log, classify and mark the historical dialogue data according to the result of the order within the set time range;

According to the historical dialogue data and the result of the classification and labeling, extract the characteristic parameters of the historical dialogue data, and process the characteristic parameters of the historical dialogue data;

According to the characteristic parameters of the processed historical dialogue data, a neural network model is established;

Using the historica...

Embodiment 2

[0045] Optionally, the neural network model establishment unit includes a first determination unit, a first encoding unit, a second encoding unit, a classification unit, a first calculation processing unit and a second determination unit:

[0046]Optionally, the acquiring unit further includes a filtering unit for filtering the historical dialogue data.

[0047] Optionally, the characteristic parameters include sentence information, role information and time information; the sentence information includes dialogue content; the character information includes the identity of the interlocutor; the time information includes the time data corresponding to the sentence information and the current dialogue and dialogue. The time interval between the previous sentence of the current conversation and the conversation data The time interval between adjacent conversations.

[0048] Optionally, the first feature extraction unit includes:

[0049] Optionally, the output unit, also includes...

Embodiment 3

Based on the same principle as the method shown in the embodiment of the present invention, the embodiment of the present invention further provides an electronic device, as shown in the accompanying Figure 4 As shown, the electronic device may include but is not limited to: a processor and a memory; a memory for storing a computer program; a processor for executing the method shown in any embodiment of the present invention by invoking the computer program.

[0051] In an optional embodiment, an electronic device is provided, Figure 4 The illustrated electronic device 40 includes a processor 410 and a memory 430 . The processor 410 is connected to the memory 430 , for example, through a bus 420 .

[0052] Optionally, the electronic device 40 may further include a transceiver 440, and the transceiver 440 may be used for data interaction between the electronic device and other electronic devices, such as data transmission and / or data reception. It should be noted that in pra...

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Abstract

The invention provides an order formation prediction method and device in a customer service dialogue process and electronic equipment. The method comprises the following steps: acquiring historical dialogue data; querying the order logs, and determining buyer order logs in a set time range; classifying and marking the historical dialogue data; feature parameters of the historical dialogue data are extracted and processed; establishing a neural network model; training the neural network model to obtain an order prediction model; collecting current dialogue data, and extracting feature parameters of the current dialogue data; inputting feature parameters of the current dialogue data; loading a form-forming prediction model, and processing the characteristic parameters by the form-forming prediction model; and outputting a prediction result of the order rate. According to the invention, the order prediction model is obtained through training of the neural network model, and the order prediction model is utilized to predict the order rate in real time in dialogue chat, so that customer service personnel can adjust dialogue behaviors in real time.

Description

technical field [0001] The present invention relates to the field of computer technology, and in particular, to a method, device and electronic device for predicting order formation in a customer service dialogue process. Background technique [0002] E-commerce sales account for a relatively high proportion of sales. During the sales process, customer service answers various questions for buyers. However, due to the differences in the ability of customer service personnel, for the same buyer, the final order result is affected by the ability of the customer service personnel. By collecting the order rate data, summarizing and summarizing the order rate data, the sales experience of the customer service personnel can be enriched; the existing technology counts the order rate, and it is necessary to accumulate multiple sets of data before it can be given posteriorly, and it is impossible to chat in a conversation. The real-time prediction of the order rate is not conducive t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/02G06Q30/00G06K9/62
CPCG06Q30/0202G06Q30/0281G06Q30/01G06F18/2415
Inventor 段佳旺江岭黄鹏郭涛
Owner CHENGDU XIAODUO TECH CO LTD