Using Genetic Programming to Evolve Weighting Schemes for the Vector Space Model of Information Retrieval
Ronan Cummins Colm O'Riordan
Term weighting in many Information Retrieval models is of crucial importance in the research and development of accurate retrieval systems. This paper explores a method to automatically determine suitable term weighting schemes for the vector space model. Genetic Programming is used to automatically evolve weighting schemes that return a high average precision. These weighting functions are tested on well-known test collections and compared to the tf-idf based weighting scheme using standard Information Retrieval performance metrics.