摘要：Recently, several search engines have been established to help people find interesting information among the rapidly increasing number of web pages over the Internet. To obtain useful and reasonable searching results, users may submit queries with more than one query terms combined by a Boolean expression, supported by all existing search engines. However, these search engines all put the same emphasis on each query term combined by the Boolean expression. That is, for the identical queries, different users would obtain the same searching results. This contradicts the fact that different users usually have different searching interests even with the same queries. In other words, a useful search engine nowadays should allow users to emphasize each query term unequally to get the more reasonable and individual searching results. In this paper we propose an efficient approach, named Extreme Score Analysis method (ESA method), to solve this problem. ESA method uses web pages' original scores to derive users' top K web pages when each query term is assigned with a different weight. Moreover, we improve ESA method and further propose Extreme Score Analysis Inverse method (ESIA method), which can efficiently find users' top K interesting target ranks when these users assign different weights to each query term
关键词：search engine; term weighting function; similarity function; ranking; Boolean expression
