一种长短期兴趣结合的个性化检索模型  

Personalized Search by Combining Long-term and Short-term User Interests

作　　者：王晓春[1] 李生[1] 杨沐昀[1] 赵铁军[1] 

机构地区：[1]哈尔滨工业大学计算机科学与技术学院,黑龙江哈尔滨150001

出　　处：《中文信息学报》2016年第3期172-177,共6页Journal of Chinese Information Processing

基　　金：国家自然科学基金(61105072&61272384);国家863计划项目(2011AA01A207)

摘　　要：个性化信息检索针对用户个人兴趣优化文档排序,被认为是改善用户检索体验的一种有效途径。为提高个性化检索模型的检索性能,该文提出了一种将用户的长短期兴趣结合的通用方法,利用用户长期兴趣和短期兴趣对查询模型进行改进。大规模真实搜索日志数据上的实验结果显示,利用长短期兴趣能够获得准确表达信息需求的查询模型,相对于传统的个性化检索模型取得了更好的效果。Personalized information retrieval tailors the ranking of documents by taking into account individual inter- ests,which has long been recognized as promising in improving the search experience. In order to improve personal- ized retrieval performance,this paper presents a general method of combining long-term and short-term interest to improve the query model. Tested on a large-scale real search log of a commercial search engine,our method can cap- ture the individual information needs more accurately and significantly outperforms the state-of-the art method.

关 键 词：个性化信息检索 长期兴趣 短期兴趣 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]