面向差异化搜索背景的查询推荐方法  

Query Recommendation Method for Differentiated Search Background

作　　者：孙达明[1] 张斌[1] 张书波[1] 马安香[1] 

机构地区：[1]东北大学信息科学与工程学院,沈阳110819

出　　处：《计算机工程》2016年第11期202-206,共5页Computer Engineering

基　　金：国家自然科学基金(61572117;61572116);宁夏回族自治区自然科学基金(NZ13265)

摘　　要：搜索引擎中存在一些用户在查询日志中保存部分搜索记录,但又不足以为用户提供个性化的查询推荐。对于此类用户,对其提供具有针对性的推荐服务能够在一定程度上提高用户对推荐结果的满意度。为此,提出一种面向不同搜索背景的差异化查询推荐方法,依据用户搜索行为将用户划分为不同群体,针对不同群体提供不同的推荐服务,实现群体用户之间的差异化推荐服务。在真实数据集上的实验结果表明,该方法能在控制推荐失败风险的同时,提高用户对推荐结果的满意度。There are some users that own some records in the search log,but it is not enough to provide the users with personalized query recommendation service.For these users,it can improve their satisfaction with recommendations results if targeted recommendation services can be provided.In order to solve the problem,this paper proposes a differentiated query recommendation method for different search background.Users are divided into different groups according to user search behavior.Different recommendation service is provided for different groups to realize differentiated recommendation service between group users.Experimental results on real datasets show that this method can reduce the risk of recommendation failure and improve the satisfaction of users for recommendation.

关 键 词：查询推荐 差异化 搜索背景 社团发现 查询流图 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]