1. A recommendation search method for reducing human-machine interactions during a search, comprising: recording a search log and a click log for query terms during search processes performed with a search engine, the search engine including at least a vertical search engine and a web search engine; determining, by a processor of the search engine, weights of tendencies of vertical searches for the query terms based on the recorded search log and click log; upon detecting a query term in a search box, determining, by the processor, recommended query terms relating to the query term in the search box, searching for the weights of tendencies of the vertical searches for each of the recommended query terms and determining a tendentious vertical search type for each of the recommended query terms based on the weights of tendencies of the vertical searches, and displaying each of the recommended query terms and links of the tendentious vertical search types for the recommended query terms; upon detecting a click on a link of one of the tendentious vertical search types corresponding to one of the recommended query terms, performing, by the processor, a search based on the one of the recommended query terms by using a vertical search engine corresponding to the one of the tendentious vertical search type, and displaying search results, wherein: the recording the search log for the query terms further includes: for each type of vertical search engine, when a search is performed with a vertical search engine of the type of vertical search engine, recording, by the vertical search engine, content of the query term being entered, the number of links being clicked among the search results, and the type of the vertical search engine, and the recording the click log for the query terms further includes: recording, by the web search engine, the content of the query term being entered, links being clicked among the search results, and the vertical search types corresponding to the links being clicked, when a search is performed with the web search engine, the determining weights of tendencies of vertical searches for the query terms based on the recorded search log and click log further includes: determining weights of the tendencies of the vertical search types for each of the query terms, a weight of tendency of a certain vertical search type being determined by: determining a first weight of the tendency of the certain vertical search type for a certain query term based on the search log, determining a second weight of the tendency of the certain vertical search type for the certain query term based on the click log, and obtaining the weight of the tendency of the certain vertical search type for the certain query term by combining the first weight of the tendency and the second weight of the tendency.
1. A recommendation search method for reducing human-machine interactions during a search, comprising: recording a search log and a click log for query terms during search processes performed with a search engine, the search engine including at least a vertical search engine and a web search engine; determining, by a processor of the search engine, weights of tendencies of vertical searches for the query terms based on the recorded search log and click log; upon detecting a query term in a search box, determining, by the processor, recommended query terms relating to the query term in the search box, searching for the weights of tendencies of the vertical searches for each of the recommended query terms and determining a tendentious vertical search type for each of the recommended query terms based on the weights of tendencies of the vertical searches, and displaying each of the recommended query terms and links of the tendentious vertical search types for the recommended query terms; upon detecting a click on a link of one of the tendentious vertical search types corresponding to one of the recommended query terms, performing, by the processor, a search based on the one of the recommended query terms by using a vertical search engine corresponding to the one of the tendentious vertical search type, and displaying search results, wherein: the recording the search log for the query terms further includes: for each type of vertical search engine, when a search is performed with a vertical search engine of the type of vertical search engine, recording, by the vertical search engine, content of the query term being entered, the number of links being clicked among the search results, and the type of the vertical search engine, and the recording the click log for the query terms further includes: recording, by the web search engine, the content of the query term being entered, links being clicked among the search results, and the vertical search types corresponding to the links being clicked, when a search is performed with the web search engine, the determining weights of tendencies of vertical searches for the query terms based on the recorded search log and click log further includes: determining weights of the tendencies of the vertical search types for each of the query terms, a weight of tendency of a certain vertical search type being determined by: determining a first weight of the tendency of the certain vertical search type for a certain query term based on the search log, determining a second weight of the tendency of the certain vertical search type for the certain query term based on the click log, and obtaining the weight of the tendency of the certain vertical search type for the certain query term by combining the first weight of the tendency and the second weight of the tendency. 2. The method of claim 1 , wherein determining a first weight of the tendency of the certain vertical search type for a certain query term based on the search log further includes: determining a search weight X/Y, wherein X indicates a number of searches based on the certain query term performed by the certain type of vertical search engine during a specified period of time, and Y indicates a number of all searches performed by the certain type of vertical search engine during the specified period of time; determining a click weight N/M, wherein N indicates a number of clicked links among the search results for the certain query term of the certain type of vertical search engine during the specified period of time, and M indicates a number of links that have been clicked among all search results in a page of the certain type of vertical search engine during the specified period of time; and obtaining the first weight of the tendency of the certain type of vertical search for the certain query term by performing a weighted calculation on the search weight and the click weight.