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              <text>Artificial Neural Networks for Enhancing E-commerce: A Study on Improving Personalization, Recommendation, and Customer Experience</text>
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              <text>AI-powered chatbots; Artificial intelligence; Artificial neural network (ANN); E-commerce; Feature selection; Machine learning</text>
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              <text>With e-commerce companies, artificial intelligence (AI) has emerged as a crucial innovation that allows companies to streamline processes, improve customer interactions, and increase operational capabilities. To provide tailored suggestions, address client care requests, and improve inventory control, AI systems may evaluate consumer data. Moreover, AI can improve pricing methods and identify fraudulent activity. Companies can actually compete and provide better consumer interactions with the growing usage of machine learning in e-commerce. This essay examines how AI is reshaping the e-commerce sector and creating fresh chances for companies to enhance their processes and spur expansion. AI technology which enables companies to enhance their procedures and offer a more individualized customer experiences has grown into a crucial component of the e-commerce sector. Purpose of providing product suggestions and improve pricing tactics, intelligent machines may examine consumer behavior, interests, and purchase history. Customer service employees will have less work to do as a result of chatbots powered by artificial intelligence handling client queries and grievances. AI may also aid online retailers in streamlining their inventory control by anticipating demands and avoiding overstocking. The use of AI technologies can also identify suspicious transactions and stop economic losses. AI is positioned to assume a greater part in the expansion and accomplishment of the e-commerce sector as it grows in popularity.  The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.</text>
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              <text>Upreti K.; Gangwar D.; Vats P.; Bhardwaj R.; Khatri V.; Gautam V.</text>
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              <text>Lecture Notes in Electrical Engineering, Vol-1115, pp. 141-153.</text>
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              <text>Springer Science and Business Media Deutschland GmbH</text>
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              <text>2024-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1007/978-981-99-8661-3_11" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-981-99-8661-3_11&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187661482&amp;amp;doi=10.1007%2F978-981-99-8661-3_11&amp;amp;partnerID=40&amp;amp;md5=12c2408067b1773d36ae19796c91446f" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187661482&amp;amp;doi=10.1007%2f978-981-99-8661-3_11&amp;amp;partnerID=40&amp;amp;md5=12c2408067b1773d36ae19796c91446f&lt;/a&gt;</text>
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              <text>ISSN: 18761100; ISBN: 978-981998660-6</text>
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              <text>Upreti K., Department of Computer Science, CHRIST (Deemed to Be University), Delhi NCR Campus, Ghaziabad, India; Gangwar D., Department of Management, ADGITM, Delhi, India; Vats P., Department of CSE, SCSE, Manipal University Jaipur, Rajasthan, Jaipur, India; Bhardwaj R., Chitkara Business School, Chitkara University, Punjab, Rajpura, India; Khatri V., Bhagwan Parshuram Institute of Technology, Delhi, India; Gautam V., Warwick Manufacturing Group, Coventry, United Kingdom</text>
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