| 摘要 |
An information retrieval system includes a query revision architecture that integrates multiple different query revisers, each implementing one or more query revision strategies. A revision server receives a user's query, and interfaces with the various query revisers, each of which generates one or more potential revised queries. The revision server evaluates the potential revised queries, and selects one or more of them to provide to the user. A confidence estimator and method provide the ability to improve the likelihood of success of suggested revised queries derived from various revision strategies. This is accomplished by tracking user queries, query revision links, results associated with revised queries, and various features of the original query and revised queries. This data is then analyzed using a predictive model to generate a set of rules that can be used to estimate the likelihood of a revised query being a successful revision for a given query.
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