论文标题
单词 - 固定在查询术语预测中的作用
The Role of Word-Eye-Fixations for Query Term Prediction
论文作者
论文摘要
在整个搜索过程中，用户对经过检查的SERP和网站的目光可以揭示其搜索兴趣。凝视行为可以通过眼睛跟踪捕获，并用文字固定来描述。 Word-eye固定包含用户在网页的每个单个单词上的累积凝视固定持续时间。在这项工作中，我们分析了单词固定在预测查询术语中的作用。我们研究了一系列课程特征，尤其是目光数据之间的关系，以及用于预测查询术语的查询术语和火车模型。我们使用通过社会科学领域的实验室研究获得的50次搜索课程的数据集。使用已建立的机器学习模型，我们可以以相当高的精度预测查询术语，即使只有很少的培训数据。功能分析表明，类别固定，查询相关性和会话主题包含我们任务最有效的功能。
Throughout the search process, the user's gaze on inspected SERPs and websites can reveal his or her search interests. Gaze behavior can be captured with eye tracking and described with word-eye-fixations. Word-eye-fixations contain the user's accumulated gaze fixation duration on each individual word of a web page. In this work, we analyze the role of word-eye-fixations for predicting query terms. We investigate the relationship between a range of in-session features, in particular, gaze data, with the query terms and train models for predicting query terms. We use a dataset of 50 search sessions obtained through a lab study in the social sciences domain. Using established machine learning models, we can predict query terms with comparably high accuracy, even with only little training data. Feature analysis shows that the categories Fixation, Query Relevance and Session Topic contain the most effective features for our task.
