Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A query submitted to a search engine provides limited information about the searcher’s real search intent. Alternatively, other information from user’s historical behaviors, e.g., clicks and dll time, can provide a strong clue to identify the search purpose. , : (1) investigate the impact of distributions of users and queries on reranking documents that are initially returned by a search engine; (2) perform tests for all users, i.e., both seen and unseen users in the training period. For unseen users,  explore the knowledge from their similar users seen in the training period. Our experiments show that integration of information from user behavior and document with an optimal ight outperforms combinations with a fixed tradeoff. On average, our model achieves near 3 % improvements than the best baseline approach in terms of metrics, e.g., MAP, P@K and NDCG@K.
['Fei Cai', 'Honghui Chen']
I am writing a research paper on a idea A Probabilistic Model for Information Retrieval by Mining User Behaviors
[{"from": "human", "value": "I am writing a research paper on a idea A Probabilistic Model for Information Retrieval by Mining User Behaviors"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A query submitted to a search engine provides limited information about the searcher\u2019s real search intent. Alternatively, other information from user\u2019s historical behaviors, e.g., clicks and dll time, can provide a strong clue to identify the search purpose. , : (1) investigate the impact of distributions of users and queries on reranking documents that are initially returned by a search engine; (2) perform tests for all users, i.e., both seen and unseen users in the training period. For unseen users,  explore the knowledge from their similar users seen in the training period. Our experiments show that integration of information from user behavior and document with an optimal ight outperforms combinations with a fixed tradeoff. On average, our model achieves near 3 % improvements than the best baseline approach in terms of metrics, e.g., MAP, P@K and NDCG@K."}]