Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Book Chapter Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conversational Agents and Chatbots: Current Trends Description An account of the resource Languages facilitate the communication and interaction process among people. Computers learn to communicate with humans intelligently with the help of conversational agents and chatbots based on Natural Language Processing (NLP). Conversational agents and chatbots are gaining popularity in various applications. The development of chatbots or conversational agents is tightly coupled with an organizations customer service requirement. However, the background procedures that power the bots brain are more or less dependent on Artificial Intelligence-based processes. NLP mechanisms powered by various Deep Learning techniques are often used in the training and development of such intelligent agents. These bots inevitably become more competent as they interact with more people. The interactions between a customer and the bot are usually used as data in further training iterations. Chatbots are likely to respond with faster and more precise suggestions leading to solutions for frequently asked questions. Therefore, the current trends indicate the need for a supplementary system rather than substituting human agents existing customer service. The customer experience and intelligence of the chatbots are improved with the help of data analysis and training with the use of Deep Learning techniques. The chapter covers the current trends of conversational agents and chatbots, how the various Artificial Intelligence techniques have transformed the development of multiple architectures of these intelligent systems, and it compares the different state-of-the-art NLP-based chatbot architectures. 2024 selection and editorial matter, Anitha S. Pillai and Roberto Tedesco. Creator An entity primarily responsible for making the resource Joseph A.; Eapen N.G. Source A related resource from which the described resource is derived Machine Learning and Deep Learning in Natural Language Processing, pp. 17-52. Publisher An entity responsible for making the resource available CRC Press Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1201/9781003296126-4" target="_blank" rel="noreferrer noopener">https://doi.org/10.1201/9781003296126-4</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173831295&amp;doi=10.1201%2F9781003296126-4&amp;partnerID=40&amp;md5=bf39bfcb76274ce0212916d5232a7711" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173831295&amp;doi=10.1201%2f9781003296126-4&amp;partnerID=40&amp;md5=bf39bfcb76274ce0212916d5232a7711</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-100096085-3; 978-103226463-9 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Joseph A., Department of Data Science, CHRIST Deemed to be University, Pune Lavasa Campus, India; Eapen N.G., Department of Data Science, CHRIST Deemed to be University, Pune Lavasa Campus, India