Automated extraction of hit numbers from search result pages

When a query is submitted to a search engine, the search engine returns a dynamically generated result page that contains the number of hits (i.e., the number of matching results) for the query. Hit number is a very useful piece of information in many important applications such as obtaining document frequencies of terms, estimating the sizes of search engines and generating search engine summaries. In this paper, we propose a novel technique for automatically identifying the hit number for any search engine and any query. This technique consists of three steps: first segment each result page into a set of blocks, then identify the block(s) that contain the hit number using a machine learning approach, and finally extract the hit number from the identified block(s) by comparing the patterns in multiple blocks from the same search engine. Experimental results indicate that this technique is highly accurate.