Nowadays, internet is important part of our life. User can explore answer to different queries according to his requirement using internet. The nature of these web resources is dynamic and they are present in huge amount. So it becomes challenge to search quality results of required query efficiently as well as personalized search is also a major challenge in Information retrieval. To handle these challenges, a two-stage framework of web crawler is proposed. In first stage, crawler performs “Reverse searching” that matches user searched query with the URL of link from site database. In second stage, crawler performs “Incremental prioritizing” that matches the searched query content with web document. Then crawler classifies relevant and irrelevant pages according to match frequency of searched keyword and ranks these pages. Proposed crawler performs searching through personalized searching according to user point of interest which is based on profession profile of user. The crawler performs the domain classification which helps user to know the contribution of standard resources of searched query. A separate log file is maintained by crawler considering the issue of searching time. While entering cursor in search box, user will get pre-query result based on past search results. Our objective is to design a Focused Crawler to effectively search the site database and provide quality result to the user.