Bill Slawski at Cre8asite Forums has a thread named Deletion Probablilities for Better Ads. In that thread he clearly explains a Yahoo! Patent named System and methods for ranking the relative value of terms in a multi-term search query using deletion prediction, the abstract reads;
The likely relevance of each term of a search-engine query of two or more terms is determined by their deletion probability scores. If the deletion probability scores are significantly different, the deletion probability score can be used to return targeted ads related to the more relevant term or terms along with the search results. Deletion probability scores are determined by first gathering historical records of search queries of two or more terms in which a subsequent query was submitted by the same user after one or more of the terms had been deleted. The deletion probability score for a particular term of a search query is calculated as the ratio of the number of times that particular term was itself deleted prior to a subsequent search by the same user divided by the number of times there were subsequent search queries by the same user in which any term or terms including that given term was deleted by the same user prior to the subsequent search. Terms are not limited to individual alphabetic words.
Bill explains the logic of the patent as a method of deleting the less relevant word, if the whole phrase of the search query does not match an ad within the ad inventory.
This could be done by looking at two word searches from users, and seeing if they might delete one of the words in a follow-up search. Search engineers might be able to set something up to find such deletions, and create a "deletion probability score" for terms.
More details at Cre8asite Forums.
