Dual brain + single process architecture: core module operating mode
Using the N-Gram model, each conversation is decomposed and vectorized to obtain feature value results. The feature value is used as a base value for vector space positioning.
Comparing vector values. In addition, user intent is initially translated into necessary additional information.
The pre-trained high-dimensional language model defines the position.
Double-checks classified results.
Identify the intended meaning of user conversation content to identify special and meaningful information from their wording.
Analyze needs and intentions of users from conversation content, classify language data, and find the correct direction to proceed.
With Elastic search, FAQ can quickly compare massive data and remove low to medium correlations. Low computing power.
6 different algorithms filter the data and give a precise scoring.
SysTalk.Chat's Intent-Based Chatbot is more accurate.
Features of FAQ
Simulate human conversations to reduce conversation fragmentation.
Finding the right answer, regardless of the way customers ask the question.
Enhanced synonymy database to improve response rate.
Advanced customer service through follow-up inquiries.
Meet the natural user behavior
Increase first-time resolution rate
Improve service efficiency
Scale your project scope