Smart Web Searches: Leveraging AI and Big Data for Personalization

Conventional search engines typically deliver the same set of output links to different users in response to the same search query, despite the variation in personalized search requirements among users. Additionally, the immense and continuously expanding nature of the web results in incomplete indexing, even by the most popular search engines. This paper addresses these issues by proposing a cloud architecture for a Meta search tool implemented through the Hadoop framework. Furthermore, current research work is extended from our previous work by incorporating ethical implications of personalized search. The extensive experimental evaluation shows that this proposed Meta search framework can surpass popular search engines in personalized search precision.