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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | PRICE NEGOTIATING CHATBOT WITH TEXT AND VOICE ON E-COMMERCE WEBSITE |
| Authors Name: | Kalwakuntla Sravan Kumar Reddy , Samala Bhanu Prakash , Uppu Bhaskar |
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IJNRD_215922
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| Published Paper Id: | IJNRD2403513 |
| Published In: | Volume 9 Issue 3, March-2024 |
| DOI: | |
| Abstract: | In recent years online shopping has gained a huge boom. With this increase, most of the features of online shopping are developed but some features like negotiating with shopkeepers are not available which is sometimes possible in offline purchasing. We have implemented a chatbot for negotiating on the products. The chatbot interacts with customers and assists them to get a satisfactory price on product(s). With such a system, which impacts on major areas of online shopping there are possibilities in which either the seller of the product or customer’s budget gets compromised. To avoid such situations we have developed an algorithm which works along with prediction of old available data to provide a price. Price prediction has less accuracy at times because either irrelevant features/attributes of data are used or some algorithms are not suitable for a particular dataset. Due to this, Ecommerce business does not directly rely on price prediction systems since even a wrong prediction of a single product can result in business losses. Some models also fail when data scales or some feature is unavailable after time on which model prediction was dependent. Then those changes are to be managed to maintain the accuracy and reliability of the model. In our chatbot system we have tried to resolve some of such issues. E-commerce websites today apply various AI techniques to determine most liked products or most sold products which eventually are calculated to provide an effortless search for customers shopping on their website. But at times when the best products are sold at high prices, customers have to compromise on their product. |
| Keywords: | Price negotiation, E-commerce negotiation, Chatbot, Machine Learning, Neural Network, Natural Language Processing. |
| Cite Article: | "PRICE NEGOTIATING CHATBOT WITH TEXT AND VOICE ON E-COMMERCE WEBSITE", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 3, page no.f103-f110, March-2024, Available :http://www.ijnrd.org/papers/IJNRD2403513.pdf |
| Downloads: | 00030 |
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2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2403513 Registration ID: 215922 Published In: Volume 9 Issue 3, March-2024 DOI (Digital Object Identifier): Page No: f103-f110 Country: Hyderabad/Medchal , Telangana , India Research Area: Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2403513 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2403513 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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