【摘要】 为提高搜索引擎的查准率,提出了一种基于群用户兴趣模型的加权全局相关度查询排序算法。算法综合考虑了用户搜索意图与搜索结果的全局相关度,改进了搜索引擎的排序结果,为用户提供了准确的搜索服务。实验结果表明,与用户意图相关的搜索结果能够排在最前面,搜索准确率明显提高。更多还原

【Abstract】 In order to improve the precision ratio of search engine,the weighted global similarity ranking algorithm based on group user interesting model was presented.The ranking algorithm integrated global similarity between the query result and the user′s search intention.The search engine ranking results were improved.The algorithm provided users with more accurate search services.The experimental results show that the precision ratio of search engine is markedly improved;the ranking algorithm can rank high relevancy results between the query result and the user′s search intention in the front of the list.更多还原