Abstract: With the rapid development of Internet economy，POI（Point Of Interest）search becomes the core technology of spatial information services.The ultimate goal of POI search engines is undoubtedly to improve customer satisfaction.Through mining user access logs and establishing the feedback similarity model，the accuracy of search results is improved.The POI search engine is optimized.Through theoretical analysis，the method improves the accuracy of the search results without extra computation time.The method is applied to Tongmap（www.tongmap.cn） which is a map search engine developed by Geographic Information Center，Institute of Computing Technology，Chinese Academy of Sciences.Finally，simulation work shows that the method is effective in POI search engine optimization.

摘要： 随着互联网经济的迅猛发展，POI（Point Of Interest）搜索成为空间信息服务业发展的核心技术之一。提高用户满意度无疑是POI搜索引擎的最终目标。通过挖掘用户访问日志，建立反馈相似度模型，可提高搜索结果准确度，优化POI搜索引擎。通过理论分析，该方法在不增加计算时间的基础上提高了搜索结果的准确性。最后将该方法应用于中国科学院计算技术研究所地理信息中心自主研发的通图（www.tongmap.cn）地图搜索引擎中，结合实际数据测试，说明该方法在优化POI搜索引擎方面是行之有效的。