In Information systems working at a large scale where retrieval of information is an essential operation for example search engines etc. The users are not only concerned with the quality of results but also the time they consume for querying the data. These aspects lead to a natural tradeoff in which the approaches that lead to an increase in data have a similar larger response time and vice-versa. Hence, as the requirement for faster search query processing time along with efficient results is increasing, we need to identify other ways for increasing efficiency. This work proposes an application of the meta-heuristic algorithm called Grey Wolf Optimization (GWO) algorithm to improve Query Processing Time in Search Engines. The GWO algorithm is an alter ego of the way in which the grey wolves are organised and their hunting techniques. There are four categories of grey wolves in a single pack of grey wolves which are alpha, beta, delta, and omega respectively. They are used to work in a simulating hierarchy. These help achieve better search results at decrease query response timings.
Site-based dynamic pruning for query processing in search engines
