One of the most prominent fields of online advertising is Sponsored search and for various search engines, it acts as one of the main sources of revenue. This paper focuses on sponsored links displayed to the user along with search results when a query is fired by the user. Bidding on keywords is done by the advertiser for the expected future queries and accordingly, payment is done if clicked. A novel technique is proposed in this paper which aims to maximize the revenue earned by a search engine by using an Adaptive keyword weighted approach. Normally, the advertisers focus on keywords with a high frequency which leads to underexplored revenue of search engines. The approach proposed in this paper assigns weight to the keywords based on their winning probability. It also merges the assigned weight with the rarity factor leading to more revenue. With this approach, advertisers with relevant keywords which are rare are explored even if the bid value is low. Experimental results are shown in this paper for proving the improvements over the generalized balance algorithm.