People constantly utilize technological advances, such as smart devices, to make their daily lives easier. The majority of those folks prefer to communicate with machines using natural language. The goal of this study is to develop a natural language search engine for purchasing and selling vehicles. When searching using text or voice, the system will provide the best results for the user. There are a few search engines where a user can search for what they need in natural language, yet the user is frustrated since the search engine does not provide the best possible results. A search in natural language, such as English, is conducted using conventional spoken language, such as Google or Bing. Users may be necessary to visit a variety of different websites and search engines while searching for vehicles and parts. When browsing for vehicles, the searcher is usually presented with a list of records rather than genuine search results due to inaccuracy and duplication of search results. People’s preferred search engine was frequently interfering with their own internet results, causing annoyance, and recurring difficulties with online search vehicles. The reason for the delay in delivering results is partly due to the volume of results that a natural language search is expected to return. This approach tries to make it easier for users to access information about vehicle purchasing and selling, as well as facts about the vehicle price process, through a specially designed mobile and web application. This system, which will be developed in both Sinhala and English, has been designed. Because of the illiteracy of the population, that system was created to conduct voice searches. Machine learning technology will be used to create this system.

Machine learning search engine natural language processing