A meta-search group recommendation mechanism based on user intent identification
Xinbao Shao, Qingshan Li, Yishuai Lin, Boyu Zhou · 2017
Recommendation mechanism is one of the most important applications for web service, and it has also been widely used in the field of information retrieval. However, traditional recommender system cannot be deployed directly in the meta-search environment. This is because that the meta-search environment doesn't have data resources owned by traditional search engines such as Internet corpus. In the process of the research on the intelligent method and technology of meta-search engine based on Agent, according to its features and user query log, this paper proposes a recommendation mechanism based on user intent identification, which builds both the common task blackboard model and the query-flow graph model in order to make full use of user behavior information generated under meta-search engine environment. Finally, the application of the mechanism in the intelligent meta-search engine based on Agent and the test data are given, which prove the mechanism to a certain extent.