Locality Based Pruning Methods for Web Search Edleno Silva de Moura and Celia Francisca dos Santos and Bruno dos Santos de Araujo and

This paper discusses a novel approach developed for static index pruning that takes into account the locality of occurrences of words in the text. We use this new approach to propose and experiment simple and effective pruning methods that allow a fast construction of the pruned index. The methods proposed here are specially useful for pruning in environments where the document database changes continuously, such as large scale web search engines. Extensive experiments are presented showing that the proposed methods can achieve high compression rates while maintaining the quality of results for the most common query types present in modern search engines, i.e. conjunctive and phrase queries. In the experiments, our locality based pruning approach allowed reducing search engine indices to 30 % of their original size, with almost no reduction in precision at the top answers. Furthermore, we conclude that even an extremely simple locality based pruning method can be competitive when compared to complex methods that do not rely on locality information