Automated parametrization of custom search ranking functions

The search for information is a task most commonly performed by web search engines. A common problem in web search is the personalization of search results. Personalization is essentially a customization of the results ranking formula. This paper focuses on the automation of the ranking formula according to the user's preferences. A genetic algorithm is used to find the proper combination of the ranking factors. The ranking function is a sum of chosen ranking factors weighted appropriately. The factors are formally described and range from simple (word count) to complex (semantic classification) in their complexity. The paper presents an approach that uses a genetic algorithm to determine the proper combination of the factors of the ranking functions. The end result gives a proper personalization of the search result ranking.