Abstract: The present disclosure relates to a question recommending method, apparatus, and system. The method includes: constructing, by a server, an interest vector of a user according to a short-term interest, a long-term interest, and a group interest of the user, the interest vector of the user including multiple interest items; acquiring a candidate-for-recommendation question from a set of to-be-resolved questions according to the multiple interest items; estimating, according to a click-through rate (CTR) model, probability of answering the candidate-for-recommendation question by the user, and selecting a to-be-recommended question according to the estimated probability; and sending the to-be-recommended question to a client. In this way, a real-time comprehensive recommendation result can be obtained, and a question answering rate of an interactive question-and-answer platform can also be improved.

Abstract: The present disclosure relates to a question recommending method, apparatus, and system. The method includes: constructing, by a server, an interest vector of a user according to a short-term interest, a long-term interest, and a group interest of the user, the interest vector of the user including multiple interest items; acquiring a candidate-for-recommendation question from a set of to-be-resolved questions according to the multiple interest items; estimating, according to a click-through rate (CTR) model, probability of answering the candidate-for-recommendation question by the user, and selecting a to-be-recommended question according to the estimated probability; and sending the to-be-recommended question to a client. In this way, a real-time comprehensive recommendation result can be obtained, and a question answering rate of an interactive question-and-answer platform can also be improved.