Artificial Intelligence for Customer Relationship Management: Human-Computer Interaction Series
Autor Boris Galitskyen Limba Engleză Paperback – 9 dec 2021
Artificial Intelligence for Customer Relationship Management leverages a number of Natural Language Processing (NLP), Machine Learning (ML), simulation and reasoning techniques to enable CRM with intelligence. An effective and robust CRM needs to be able to chat with customers, providing desired information, completing their transactions and resolving their problems. It introduces a systematic means of ascertaining a customers’ frame of mind, their intents and attitudes to determine when to provide a thorough answer, a recommendation, an explanation, a proper argument, timely advice and promotion or compensation. The author employs a spectrum of ML methods, from deterministic to statistical to deep, to predict customer behavior and anticipate possible complaints, assuring customer retention efficiently.
Providing a forum for the exchange of ideas in AI, this book provides a concise yet comprehensive coverage of methodologies, tools, issues, applications, and future trends for professionals, managers, and researchers in the CRM field together with AI and IT professionals.
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Specificații
ISBN-13: 9783030521691
ISBN-10: 3030521699
Pagini: 460
Ilustrații: XI, 445 p. 261 illus., 147 illus. in color.
Dimensiuni: 155 x 235 x 25 mm
Greutate: 0.69 kg
Ediția:1st ed. 2020
Editura: Springer
Colecția Human-Computer Interaction Series
Seria Human-Computer Interaction Series
Locul publicării:Cham, Switzerland
ISBN-10: 3030521699
Pagini: 460
Ilustrații: XI, 445 p. 261 illus., 147 illus. in color.
Dimensiuni: 155 x 235 x 25 mm
Greutate: 0.69 kg
Ediția:1st ed. 2020
Editura: Springer
Colecția Human-Computer Interaction Series
Seria Human-Computer Interaction Series
Locul publicării:Cham, Switzerland
Cuprins
Introduction.- Distributional Semantics for CRM: Making word2vec Models Robust by Structurizing Them.- Employing Abstract Meaning Representation to Lay the Last Mile towards Reading Comprehension.- Summarized Logical Forms for Controlled Question Answering.- Summarized Logical Forms based on Abstract Meaning Representation and Discourse Trees.- Acquiring New Definitions of Entities.- Inferring Logical Clauses for Answering Complex Multi-hop Open Domain Questions.- Managing Customer Relations in an Explainable Way.- Recognizing Abstract Classes of Text Based on Discourse.- Conversational Explainability for CRM
Textul de pe ultima copertă
This research monograph brings AI to the field of Customer Relationship Management (CRM) to make a customer experience with a product or service smart and enjoyable. AI is here to help customers to get a refund for a canceled flight, unfreeze a banking account or get a health test result. Today, CRM has evolved from storing and analyzing customers’ data to predicting and understanding their behavior by putting a CRM system in a customers’ shoes. Hence advanced reasoning with learning from small data, about customers’ attitudes, introspection, reading between the lines of customer communication and explainability need to come into play.
Artificial Intelligence for Customer Relationship Management leverages a number of Natural Language Processing (NLP), Machine Learning (ML), simulation and reasoning techniques to enable CRM with intelligence. An effective and robust CRM needs to be able to chat with customers, providing desired information, completing their transactions and resolving their problems. It introduces a systematic means of ascertaining a customers’ frame of mind, their intents and attitudes to determine when to provide a thorough answer, a recommendation, an explanation, a proper argument, timely advice and promotion or compensation. The author employs a spectrum of ML methods, from deterministic to statistical to deep, to predict customer behavior and anticipate possible complaints, assuring customer retention efficiently.
Providing a forum for the exchange of ideas in AI, this book provides a concise yet comprehensive coverage of methodologies, tools, issues, applications, and future trends for professionals, managers, and researchers in the CRM field together with AI and IT professionals.
Artificial Intelligence for Customer Relationship Management leverages a number of Natural Language Processing (NLP), Machine Learning (ML), simulation and reasoning techniques to enable CRM with intelligence. An effective and robust CRM needs to be able to chat with customers, providing desired information, completing their transactions and resolving their problems. It introduces a systematic means of ascertaining a customers’ frame of mind, their intents and attitudes to determine when to provide a thorough answer, a recommendation, an explanation, a proper argument, timely advice and promotion or compensation. The author employs a spectrum of ML methods, from deterministic to statistical to deep, to predict customer behavior and anticipate possible complaints, assuring customer retention efficiently.
Providing a forum for the exchange of ideas in AI, this book provides a concise yet comprehensive coverage of methodologies, tools, issues, applications, and future trends for professionals, managers, and researchers in the CRM field together with AI and IT professionals.
Caracteristici
Offers a foundation for making CRM applications intelligent Provides formalisms to determine human attitude and behavior so that a CRM system can better communicate with and guide customers Enriches a hands-on experience with CRM automation Includes complete instructions for building a chatbot for a CRM that provides customers with information, attempts to resolve their problems and complaints, as well as performing transactions for them
Notă biografică
Prof. Boris Galitsky is a cofounder of Knowledge Trail, San Jose, CA, and teaches a course on LLM-based programming at Stavropol Agrarian University. He has contributed linguistic and machine learning technologies to Silicon Valley start-ups as well as to companies such as eBay and Oracle for over 25 years. His work in information extraction and sentiment analysis supported several acquisitions, including Xoopit by Yahoo, Uptake by Groupon, LogLogic by Tibco, and Zvents by eBay. His security-related document analysis technologies also contributed to the acquisition of Elastica by Symantec.
As an architect of the Intelligent Bots project at Oracle, he developed a discourse analysis technique for dialogue management and documented this work in his book Developing Enterprise Chatbots. He also authored a two-volume monograph, AI for CRM, based on his experience developing Oracle Digital Assistant. In addition, he is an Apache committer to OpenNLP, where he created the OpenNLP Similarity component, a foundation for semantically enriched search engines and chatbot development.
Prof. Galitsky’s research into the exploration and formalization of human reasoning culminated in his book Computational Autism, widely used by parents of children with autism and rehabilitation specialists. His focus on medical applications has resulted in two further research monographs: Artificial Intelligence for Healthcare Applications and Management, co-authored with Dr. Saveli Goldberg, and Health Applications of Neuro-Symbolic Artificial Intelligence.