Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Understanding users'search intent expressed through their search queries is crucial to b search and online advertisement. b query classification (QC) has been widely studied for this purpose. Most previous QC algorithms classify individual queries without considering their context information. Hover, as exemplified by the ll-known example on query "jaguar", many b queries are short and ambiguous, whose real meanings are uncertain without the context information. ,  incorporate context information into the problem of query classification by using conditional random field (CRF) models. In our approach,  use neighboring queries and their corresponding clicked URLs (b pages) in search sessions as the context information.  perform extensive experiments on real world search logs and validate the effectiveness and effciency of our approach.  show that  can improve the F1 score by 52% as compared to other state-of-the-art baselines.
['Huanhuan Cao', 'Derek Hao Hu', 'Dou Shen', 'Daxin Jiang', 'Jian-Tao Sun', 'Enhong Chen', 'Qiang Yang']
I am writing a research paper on a idea Context-aware query classification
[{"from": "human", "value": "I am writing a research paper on a idea Context-aware query classification"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Understanding users'search intent expressed through their search queries is crucial to b search and online advertisement. b query classification (QC) has been widely studied for this purpose. Most previous QC algorithms classify individual queries without considering their context information. Hover, as exemplified by the ll-known example on query \"jaguar\", many b queries are short and ambiguous, whose real meanings are uncertain without the context information. ,  incorporate context information into the problem of query classification by using conditional random field (CRF) models. In our approach,  use neighboring queries and their corresponding clicked URLs (b pages) in search sessions as the context information.  perform extensive experiments on real world search logs and validate the effectiveness and effciency of our approach.  show that  can improve the F1 score by 52% as compared to other state-of-the-art baselines."}]