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Retail

Customer Sentiment Analysis

Deep learning-based user intent recognition

Deep learning-based user intent recognition

For:
Users
Goal:
Other
Problem addressed
To recognize and understand users intent using AI and deep learning
technologies and apply such technologies to build chat bot systems to further
reduce labour costs and for use in various fields.
Scope of use case
Recognizing users intent in order to solve their problems in e-commerce fields.
Description
JD.com has been committed to using technology to drive
business growth and improve the user experience in all
customer service fields. Based on improved customer
consulting experience and the developing trend of artificial
intelligence technology, JD had decided, as early as 2012, to
develop intelligent chat bots to fulfil the needs of its
continuously expanding business, to save on customer
service costs and to increase service capability. Intent
recognition is a key and core technology for building this
type of intelligent customer service chat bot. By applying
natural language processing technologies, deep learning
technologies, and traditional machine learning algorithms,
intent recognition accuracy has reached 95 %. Based on
accurate intent recognition and a series of solution-finding
algorithms, our chat bot can solve the users problems in
most cases and give the user a high quality consulting
experience. Finally, in order to provide diversified and
personalized customer services, we are continuously
improving the accuracy of intent recognition, personalized
solution generation, sentiment recognition, and image
recognition. So far, intelligent customer service has
revolutionized the traditional customer service consulting
business.
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Deep learning
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