Personalized search refers to search experiences that are tailored specifically to an individual's interests by incorporating information about the individual beyond specific query provided. Especially people working in a software development organization (analysts, developers, testers, maintenance team members), find it increasingly difficult to get relevant results to their searches. We propose methods to personalize searches by resolving the ambiguity of query terms, and increase the relevance of search results in order to match the user’s interests. Difficulty in web searches has given rise to the need for development of personalized search engines. Personalized search engines create user profiles to capture the users’ personal preferences and as such identify the actual goal of the input query. Since users are usually reluctant to explicitly provide their preferences due to the extra manual effort involved, the search engine faces the entire burden of predicting the user’s preferences and intentions behind a query in order to yield more relevant search results. In this paper we define a QUEST to be the objective of user’s search; here we combine quest level analysis of user’s search logs and semantic analysis of the user’s query in order to personalize user’s search results. Most personalization methods focus on the creation of one single profile for a user and apply the same profile to all of the user’s queries. Hence we propose a personalized search for a software development organization by creating QUEST or domain based profile rather than individual user based profile.