An effective and efficient algorithm for ranking web documents via genetic programming
Ricardo A. Baeza-Yates, Alfredo Cuzzocrea, Domenico Crea, Giovanni Lo Bianco · 2019
We propose an effective and efficient algorithm for ranking web documents, called CombGenRank. This algorithm introduces a novel selection criterion in the classical genetic programming paradigm, which already proved to be effective for supporting web document ranking, called elitism. Extensive experimental results conducted on top of well-known web document collections confirm the benefits deriving from our proposed approach. This algorithm is motivated by search services based on cloud computing.