Long Query User Satisfaction Analysis Based on User Behaviors

Performance evaluation is one of the most important issues in web search. Long queries contain much information which describes user 's information demand correctly. Thus,a long query search user satisfaction detection framework is proposed. The concept of user satisfaction is defined. The relevant user behavior features in user logs are extracted which are combined with Decision Tree and SVM to identify satisfactory or unsatisfactory queries. The experimental results on large scale practical search engine data show the effectiveness of the proposed framework. Furthermore,the classification accuracies of satisfactory and unsatisfactory queries reach 86% and 70% ,respectively.