Author: Zen and the Art of Computer Programming
Intelligent customer service (English: Artificial intelligence (AI) chatbot), also known as chatbot, chat assistant, etc., refers to a virtual agent driven by data based on text, sound, images and other related information, which can interact with users in real-time and Technology systems for effective, automated communication. Its main functions include: providing personalized services by tracking customer needs, understanding language, and learning conversation skills; processing data through conversation engines, natural language processing (NLP), deep learning, speech recognition and other technologies to achieve customer service tasks Automation and intelligence; improve customer satisfaction and loyalty by analyzing data and feeding back optimized products and services to customers. Intelligent marketing (English: Artificial Intelligence (AI) marketing) is a new way of marketing that uses machine learning, data mining and other computing technologies. By collecting, organizing, analyzing and mining user data, we can intelligently recommend products, services or promotion methods suitable for users, reduce marketing costs, improve marketing efficiency, and enhance customer satisfaction. At present, many companies focus their research in this field on mobile Internet, social media, e-commerce, finance and other industries.
In recent years, with the rapid development of AI technology, the increasing popularity of the Internet, and the accumulation of massive user data, people are paying more and more attention to how to realize the application of intelligent customer service and intelligent marketing through technology. In this context, text analysis technology (Text Analysis Technology) is particularly important.
Text analysis technology refers to computer technology that extracts, analyzes and mines valuable information from a piece of text, voice, pictures, videos, and knowledge bases. Traditional text analysis methods generally extract information and analyze data through technologies such as word segmentation, part-of-speech tagging, word frequency statistics, keyword extraction, classification models, and cluster analysis. Modern text analysis technology can cover the following aspects: machine learning, information retrieval, information retrieval, natural language processing, semantic analysis, graph analysis, data mining, pattern mining, biological information, biological information, etc.
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