Comparison of Meta-heuristic Algorithms for Web Link Prioritization - Chaudhary, Kamika; Gupta, Neena (International Journal of Computer Sciences and Engineering, 2019)
Technological advancement in all the fields leads to the problem of information overload in front of internet user. It has become extremely difficult for them to reach to the information which is most relevant to their need. Information gigantic size makes the user to wander from one web page to another in order to reach to their target information. This leads to wastage of user time and also reduces the interest of user from the search engine, websites as well as internet. The problem of accessing user relevant web pages falls into the category of NP-Complete problems. Web Mining, an application of data mining is utilized to find the solution of this issue of information extraction. For retrieving the relevant data top T web links needs to be prioritized. Here we propose a memetic algorithm and simulated annealing algorithm for selecting the most relevant web document. Both the algorithms are compared on the basis of their performance experimentally and results shows the domination of one over another.