BeeRank: A Heuristic Ranking Model to Optimize the Retrieval Process

There is an incredible change in the world wide web, and the users face difficulty in accessing the needed information as per their need. Different algorithms are devised at each step of the information retrieval process, and it is observed that ranking is one of the core ingredients of any search engine that plays a major role in arranging the information. In this regard, different measures are adopted for ranking the web pages by using content, structure, or log data. The BeeRank algorithm is proposed that provides quality results, which is inspired by the artificial bee colony algorithm for web page ranking and uses both the structural and content approach for calculating the rank value and provides better results. It also helps the users in finding the relevant web pages by minimizing the computational complexity of the process and achieves the result in minimum time duration. The working is illustrated and is compared with the traditional PageRank algorithm that incorporates only structural links, and the result shows an improvement in ranking and provides user-specific results.