We are living in a world in which abundant information is publicly available. As this information significantly grows, searching precisely and efficiently becomes a necessity. Unfortunately, the existing search engines fail to provide high quality search results with a good user interface. First, the search engines rank pages based on the popularity of those pages. Popularity, instead of being the result of the content is based on the hyperlinks to the pages. As a result, the application domains of existing search engines is restricted to those that can provide additional information such as hyperlinks. Second, current search engines return unsatisfactory results if the users fail to input the expected precise word/s. To remedy this specific shortcoming, our work provides relationship among the inputed words and the summarized contents using the modification relation and contents so as to assist users in choosing appropriate words as well as guess each page's content easier. Case studies were conducted to compare our research with google in terms of our ranking algorithm's efficiency and quality of user interface. The results of the case studies are encouraging and suggest users can search faster with better accuracy regardless of their prior searching expertise.