Learning Ranking Functions By Genetic Programming Revisited

We revisit the use of Genetic Programming (GP) to learn ranking functions in the context of web documents, by adding linking information. Our results show that GP can cope with larger sets of features as well as bigger document collections, obtaining small improvements over the state-of-the-art of GP learned functions applied to web search.