Patent Document ID: 8527509
Application ID: 13070265

Base Claim:
1. A search method, comprising: receiving a search request from a search client; extracting a user interest model from user personalized data according to the search request; obtaining a meta index of each member engine; selecting a member engine according to the meta index of each member engine, the search request, and the user interest model; and sending the search request to the selected member engine, so as to enable the selected member engine to complete searching; wherein the user interest model is a vector formed with scores given to each of several interest dimensions denoting user interests; the user interest model comprises a static interest model and a dynamic interest model: the static interest model is obtained by obtaining frequencies of words belonging to a certain interest dimension in a static user profile of a user, calculating a sum of the frequencies of the words belonging to the interest dimension as a score of the interest dimension, and forming a score vector with different scores to create a static interest model; and the dynamic interest model is obtained by obtaining frequencies of words belonging to a certain interest dimension in a document clicked in a search history of a user, calculating a sum of the frequencies of the words belonging to the interest dimension in the document as a score specific to the interest dimension in the document, forming a score vector specific to the document with different scores specific to different interest dimensions, and a sum of the score vectors specific to different documents to create a dynamic interest model.

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Claim 3:
3. The method according to claim 1 , wherein: receiving the search request, and sending the search request to the selected member engine are completed by a search server; and extracting the user interest model and selecting the member engine comprise: sending, by the search server, the search request to a scheduling server; extracting, by the scheduling server, the user interest model from the user personalized data according to the search request, and selecting the member engine according to the meta index of each member engine, the search request, and the user interest model; and sending, by the scheduling server, the selected member engine to the search server.