Price Negotiator E-commerce Chatbot System Source Code Free Download

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Tuula Rud

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Jan 21, 2024, 9:03:11 AM1/21/24

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Chatbots have been used in many fields ranging from education to healthcare and are also used in e-commerce settings. This research aims at developing a web-based chatbot called Hebron for the Covenant University Community Mall. The chatbot is developed using Python and React.js as the programming languages and MySQL (Structured Query Language) server as the database to give a structure to the e-commerce datasets and Admin Portal process. The e-commerce chatbot application for Covenant University Shopping Mall (CUSM) seeks to provide an easy, smart, and comfortable shopping experience for the Covenant University Community.

price negotiator e-commerce chatbot system source code free download

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The paper is organized as follows. Section 1 presents a brief overview of the project. A comprehensive review of relevant pieces of literature relating to the e-commerce chatbot is discussed in Section 2. Section 3 is the system design, where the actual design of the developed chatbot and its capabilities are presented. The results and user testing data are presented in Section 4. Section 5 is the concluding chapter, where a conclusion and relevant recommendations are stated.

In this work, a chatbot will be implemented to solve an e-commerce problem within an academic environment, specifically Covenant University, Ota. Therefore, the goal of this literature review is to study the application of chatbots in various contexts. In the section that follows, studies related to the application of chatbots in e-commerce and non-e-commerce contexts are examined to identify a gap concerning the concept of chatbots within the literature.

NLP explores how computers can understand and manipulate natural language text or speech to do useful things [23]. Ontology-based chatbots can also be implanted on e-commerce websites, according to Vegesna et al. [24]. The authors propose that the ontology-based chatbot will satisfy the user in terms of solid replies and a more natural and interesting conversation. Unlike ontology-based chatbots, pattern-based chatbots have preprogrammed responses, which makes their conversation unnatural [25].

The review of chatbot studies undertaken thus far in this section reveals that pattern-based chatbots have limited intelligence. Scholars have suggested that the AI abilities and datasets of chatbots need to be improved upon. Based on this identified gap, my proposed project aims to improve on the limited intelligence of chatbots. To implement the work, methodologies that will be utilized are React.js to build the chatbot front-end and admin login page, Spacy and React.ai for the NLP section and training of the chatbot, and e-commerce datasets for the chatbot data layer coupled with MySQL to help manage and build the data structure in which the e-commerce datasets will be stored. In the next section, the methodologies for implementing the work are described.

The chatbot interface is developed using React.js, a front-end framework for building single-page web applications. Also, React.js helps in developing responsive web pages. This is the presentation layer where users (students/staff) can fully interact with Hebron (chatbot) and get correct and up-to-date responses. Hebron is the official customer care service for CUSM. Here, the user can ask the bot questions concerning current products available, the current prices of the products sold in the shopping mall, and closing and opening times of CUSM and pay for the items the user desires to purchase via CUSM's payment platform.

Developed using MySQL, the data layer gives a structure to the e-commerce datasets that the chatbot will use to answer product-related questions. This structure, which is in the form of tables, will help the administrator (s) of CUSM put the relevant information in the right place. The structure is subdivided as follows:(1)User(2)Store(3)Purchases

Figure 5(a) shows the chatbot interface where the user-to-chatbot interaction occurs. The chatbot interface is where users (students or staff) can fully interact with the chatbot Hebron and get correct and up-to-date responses. Hebron is the official customer care service for CUSM where the user gets to ask the bot questions concerning current products available, the current prices of the products sold in the shopping mall, and closing and opening times of CUSM and pay for items via CUSM's payment platform. Figure 5(b) shows the user requesting the availability of an item and its price. Figures 5(c) and 5(d) show the payment process.

Developed using MySQL, the data layer gives a structure to the e-commerce datasets that the chatbot will use to answer product-related questions. This structure, which is in the form of tables, will help the administrator(s) of CUSM put the relevant information in the right place. The structure is subdivided as follows:(1)User(2)Store(3)Purchases

DialoGPT helps you to create high-quality NLP applications and chatbots quickly. It is an effective and simple-to-use open-source AI language tool formulated as an autoregressive (AR) language model. It processes hundreds of Gigabytes of colloquial data to generate responses using pre-training techniques. DialoGPT uses a multi-layer transformer architecture.

This chatbot is among the best AI chatbots, similar to ChatGPT, which helps research by speeding up, simplifying, and improving online searches. You can research concepts, compose emails, write code, translate text, explain opinions, and suggest ideas.