Using association rules to discover search engines related queries

Abstract

We present a method for automatic generate suggestions of related queries submitted to Web search engines. The method extracts information from the log of past submitted queries to search engines using algorithms for mining association rules. Experimental results were performed on a log containing more than 2.3 million queries submitted to a commercial searching engine giving correct suggestions in 90.5% of the top 5 suggestions presented for common queries extracted from a real log.