A Proposed Semantically Enhanced Search Engine Framework to Extract Relevant Information in the Context

As the amount of information accessible on the World Wide Web continues to increase, it is becoming apparent that General Search Engines such as Google and Yahoo are losing their effectiveness in facilitating information access. In order for search engines to achieve success, it is imperative that the information presented to the user is both pertinent and reliable. The given paper introduces a modular framework for a Search Engine that prioritizes the consolidation of dispersed data pertaining to entertainment, leisure, and travel, followed by customization of the data to cater to the unique preferences of individual users. The findings of the proposed search engine includes gathering reliable information pertaining to diverse attractions, apply a filtering mechanism, and subsequently display only the relevant pieces of information to the user. By limiting the scope of crawled websites and implementing personalized techniques, the process of retrieving information can be optimized for increased efficiency and accuracy within this category.