3. The method for mobile search according to claim 1 , wherein the calculating the relevance score value of each of the member engines according to meta index information of the member engine, the instant interest model, and the long-term interest model comprises: calculating a first maximum similarity between the keyword information and the meta index information of the member engine; calculating a second maximum similarity between the meta index information of the member engine and the instant interest model based on that a similarity between the meta index information of the member engine and the keyword information is greater than a first threshold value and a similarity between the meta index information of the member engine and the long-term interest model is greater than a second threshold value; calculating a third maximum similarity between the meta index information of the member engine and the long-term interest model based on that the similarity between the meta index information of the member engine and the keyword information is greater than a third threshold value and a similarity between the meta index information of the member engine and the instant interest model is greater than a fourth threshold value; calculating a fourth maximum similarity between the meta index information of the member engine and a resulting vector of a weighted sum of the long-term interest model and the instant interest model based on that the similarity between the meta index information of the member engine and the keyword information is greater than a fifth threshold value; and calculating a similarity score value of the member engine according to the first maximum similarity, the second maximum similarity, the third maximum similarity, and the fourth maximum similarity.
4. The method for mobile search according to claim 3 , wherein the calculating the similarity score value of the member engine according to the first maximum similarity, the second maximum similarity, the third maximum similarity, and the fourth maximum similarity comprises: acquiring the similarity score value by adding up the first maximum similarity, the second maximum similarity, the third maximum similarity, and the fourth maximum similarity in a weighted manner, or by multiplying the first maximum similarity by the second maximum similarity, the third maximum similarity, and the fourth maximum similarity, or by acquiring a maximum value among the first maximum similarity, the second maximum similarity, the third maximum similarity, and the fourth maximum similarity.