1. A method of ordering search results, comprising: obtaining exposed log files from a log system; computing Bayesian posterior probabilities for relevancy between the exposed log files and a search request; computing expected values of the relevancy between the exposed log files and the search request; storing the search request and identifiers of the exposed log files as keys and the expected values of the relevancy between the exposed log files and the search request as respective values into a search data structure; in response to receiving a search request submitted by a user, finding expected values of relevancy between the search request submitted by the user and log files that are relevant to the submitted search request from the search data structure; and ordering the found log files according to a descending order of the found expected values, wherein prior to computing the Bayesian posterior probabilities, the method further comprises filtering the exposed log files based on global parameters to filter a log file having a respective global parameter less than a predefined threshold, wherein computing the Bayesian posterior probabilities comprises computing Bayesian posterior probabilities for relevancy between the filtered log files and the search request.
1. A method of ordering search results, comprising: obtaining exposed log files from a log system; computing Bayesian posterior probabilities for relevancy between the exposed log files and a search request; computing expected values of the relevancy between the exposed log files and the search request; storing the search request and identifiers of the exposed log files as keys and the expected values of the relevancy between the exposed log files and the search request as respective values into a search data structure; in response to receiving a search request submitted by a user, finding expected values of relevancy between the search request submitted by the user and log files that are relevant to the submitted search request from the search data structure; and ordering the found log files according to a descending order of the found expected values, wherein prior to computing the Bayesian posterior probabilities, the method further comprises filtering the exposed log files based on global parameters to filter a log file having a respective global parameter less than a predefined threshold, wherein computing the Bayesian posterior probabilities comprises computing Bayesian posterior probabilities for relevancy between the filtered log files and the search request. 5. The method as recited in claim 1 , wherein computing the Bayesian posterior probabilities comprises: based on whether the user has clicked a particular log file, whether the user has seen the particular log file, a degree of relevancy between the particular log file and the search request of the user, whether the user has browsed subsequent log files and clicking conditions of previous log files, and/or if a prior distribution follows a uniform distribution over [0, 1], computing a joint posterior distribution for relevancy between the particular log file and the search request after the user clicks the particular log file.