2. The method of claim 1 , wherein the value that is indicative of a correlation between the subset of query attribute values and dissatisfaction of users of the search engine is computed as a function of a probability of the subset of query attribute values occurring in a dissatisfied query divided by a product of: a probability of the subset of query attribute values occurring in any query; and a probability of a query being a dissatisfied query.
1. A method that is executed by a computer processor on a computing device, the method comprising: receiving queries labeled as being dissatisfied queries from a computer-readable data storage device, wherein a dissatisfied query is a query submitted to a search engine by a user who was dissatisfied with search results retrieved by the search engine when provided with the query; receiving queries labeled as being satisfied queries, wherein a satisfied query is a query submitted to the search engine by a user who was satisfied with search results retrieved by the search engine when provided with the query; receiving query attribute values for each dissatisfied query and for each satisfied query; for a subset of query attribute values observed for at least one dissatisfied query, computing a value that is indicative of a correlation between the subset of query attribute values and dissatisfaction of users of the search engine, wherein the value is computed based at least in part upon the queries labeled as being dissatisfied queries, the queries labeled as being satisfied queries, and the query attribute values; and learning a segment-specific ranker based at least in part upon the value that is indicative of the correlation between the subset of query attribute values and dissatisfaction of the users of the search engine, wherein the segment-specific ranker is selected from amongst a plurality of possible rankers for ranking documents responsive to receipt of a query having the subset of query attribute values.