Authors - Khush Zambare, Amol Wagh, Sukhada Mahale, Mayank Sohani Abstract - In the all-digital world of today, the search engines are more of entry points to knowing most things. In this regard, most search engines often service the general user; most other needs, specific to a profession, go unattended. Use of "Amazon" will return results for the e-commerce giant, even when the user is the environmental scientist looking for something about the Amazon rainforest or the cloud developer searching for Amazon Web Services (AWS). This generic approach leads to inefficiencies as users need to sift through lots of useless information. This paper allows for a browser extension that personalizes the result of search on Artificial Intelligence and Machine Learning, with the aim of catering to individual users, based on their profession, interests, and specific needs. The solution dynamically re-ranks the search results as it learns from user behavior and search patterns to provide the most relevant information to save the precious time of the users. The paper will discuss current trends in SEO, AIML applications, and personalization techniques to outline how this solution can revolutionize the search engine experience.
Open Zoom
