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除了动态心电图:作为一个成功的搜索用户行为预测

Beyond DCG: User Behavior as a Predictor of a Successful Search
课程网址: http://videolectures.net/wsdm2010_hassan_bdub/  
主讲教师: Ahmed Hassan
开课单位: 密歇根大学
开课时间: 2010-10-12
课程语种: 英语
中文简介:
传统上,Web搜索引擎是根据网页与单个查询的相关性进行评估的。但是,网页的相关性并不能说明完整的情况,因为单个查询可能只代表用户的一部分信息需求,而用户在同一查询下可能有不同的信息需求。我们通过建模用户行为来解决预测用户搜索目标成功的问题。我们根据经验表明,用户行为本身可以准确反映用户的网络搜索目标的成功情况,而无需考虑所显示文档的相关性。事实上,我们的实验表明,使用用户行为的模型比使用文档相关性的模型更能预测目标的成功。我们为这项任务建立了新的包含时间分布的序列模型,实验表明,序列和时间分布模型比基于用户行为的静态模型或基于文档相关性的预测模型更精确。
课程简介: Web search engines are traditionally evaluated in terms of the relevance of web pages to individual queries. However, relevance of web pages does not tell the complete picture, since an individual query may represent only a piece of the user’s information need and users may have different information needs underlying the same queries. We address the problem of predicting user search goal success by modeling user behavior. We show empirically that user behavior alone can give an accurate picture of the success of the user’s web search goals, without considering the relevance of the documents displayed. In fact, our experiments show that models using user behavior are more predictive of goal success than those using document relevance. We build novel sequence models incorporating time distributions for this task and our experiments show that the sequence and time distribution models are more accurate than static models based on user behavior, or predictions based on document relevance.
关 键 词: 计算机科学; 网页搜索引擎; 静态模型
课程来源: 视频讲座网
最后编审: 2020-03-23:chenxin
阅读次数: 45