A two-stage mixture model for pseudo feedback

Pseudo feedback is a commonly used technique to improve information retrieval performance. It assumes a few top-ranked documents to be relevant, and learns from them to improve the retrieval accuracy. A serious problem is that the performance is often very sensitive to the number of pseudo feedback documents. In this poster, we address this problem in a language modeling framework. We propose a novel twostage mixture model, which is less sensitive to the number of pseudo feedback documents than an effective existing feedback model. The new model can tolerate a more flexible setting of the number of pseudo feedback documents without the danger of losing much retrieval accuracy.

• Type: Conference
• Year: 2004
• Where: SIGIR
• Authors: Tao Tao, ChengXiang Zhai
• Keywords: Pseudo Feedback, Pseudo Feedback Documents, Retrieval Accuracy, SIGIR 2004