Search intent estimation from user's eye movements for supporting information seeking
Search intent estimation from user's eye movements for supporting information seeking
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DOI：
10.1145/2254556.2254624
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发表时间：
2012-05
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影响因子：
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通讯作者：
Kazutoshi Umemoto;Takehiro Yamamoto;S. Nakamura;Katsumi Tanaka
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文献类型：
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作者：
Kazutoshi Umemoto;Takehiro Yamamoto;S. Nakamura;Katsumi Tanaka
在本文中，我们提出了一个两阶段的系统，使用用户的眼球运动，以适应日益增长的需求，以获得信息的Web在一个有效的方式。在第一阶段中，系统估计用户的搜索意图作为一组加权项提取的基础上，用户的眼睛运动，而浏览网页。然后在第二阶段，系统通过使用估计的意图对搜索结果进行重新排序、建议基于意图的查询以及强调网页的相关部分来向用户显示相关信息。该系统旨在帮助用户有效地获得他们所需要的重复这些步骤在整个信息搜索过程。我们提出了四种类型的搜索意图估计方法（MLT，nMLT，DLT和nDLT）考虑意图，词频和眼球运动之间的关系。作为一个实验的结果，设计用于评估每种方法的准确性与原型系统，我们证实了nMLT方法的效果最好。此外，通过分析实验中8个受试者提取的意图术语，我们发现，即使他们执行相同的搜索任务，系统也可以估计每个用户的独特搜索意图。
In this paper, we propose a two-stage system using user's eye movements to accommodate the increasing demands to obtain information from the Web in an efficient way. In the first stage the system estimates a user's search intent as a set of weighted terms extracted based on the user's eye movements while browsing Web pages. Then in the second stage, the system shows relevant information to the user by using the estimated intent for re-ranking search results, suggesting intent-based queries, and emphasizing relevant parts of Web pages. The system aims to help users to efficiently obtain what they need by repeating these steps throughout the information seeking process. We proposed four types of search intent estimation methods (MLT, nMLT, DLT and nDLT) considering the relationship among intents, term frequencies and eye movements. As a result of an experiment designed for evaluating the accuracy of each method with a prototype system, we confirmed that the nMLT method works best. In addition, by analyzing the extracted intent terms for eight subjects in the experiment, we found that the system could estimate the unique search intent of each user even if they performed the same search tasks.