Web page retrieval plays a major role nowadays. The proposed system helps in the development of optimized web page recommendation. The proposed system is a novel method to provide the web pages effectively and accurately by using genetic algorithm. First the entered query is pre-processed and similar word set is generated. It uses word net tool for semantic keyword set generation that is the various fields where that particular word is used. This tool uses the ontology concept for the keyword generation. The user has to click a word from these keyset or directly click the pre-processed word. The selected keyword is given as input to server and some webpages will be retrieved. The web contents are extracted from these webpages. Then the weightage of that particular word is calculated in all the documents/web contents retrieved. Weight Enhanced genetic algorithm which involves three main process that is selection, crossover and mutation is applied to the weights calculated. Finally, the webpage with highest weightage will be displayed first and then consequently remaining webpages will be displayed in the same manner.
Rose, J. D., Komala, J., & Krithiga, M. (2016). Efficient Webpage Retrieval Using WEGA. In Procedia Computer Science (Vol. 87, pp. 281–287). Elsevier B.V. https://doi.org/10.1016/j.procs.2016.05.162