A Reference Dependence Approach to Enhancing Early Prediction of Session Behavior and Satisfaction
A Reference Dependence Approach to Enhancing Early Prediction of Session Behavior and Satisfaction
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DOI：
10.1145/3529372.3533294
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发表时间：
2022-06
期刊：
影响因子：
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通讯作者：
T. Brown;Jiqun Liu
中科院分区：
文献类型：
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作者：
T. Brown;Jiqun Liu
行为经济学和决策科学的大量证据表明，在不确定的决策背景下，行动背后的价值载体是相对于参考点（例如行动前的预期）定义的收益和损失，而不是绝对的最终结果。此外，早期预测会话级搜索决策和用户体验的能力对于开发被动式和主动式搜索推荐至关重要。为了解决这些研究空白，我们的研究旨在 1）基于会话的第一个查询段中的一系列模拟用户期望或参考点来开发参考依赖特征，2）检查我们可以通过构建和使用参考依赖特征来增强早期预测会话行为和用户满意度的性能的程度。基于三个不同类型的数据集的实验结果，我们发现，将在第一个查询段中开发的参考相关特征合并到预测模型中，比仅在早期预测三个关键会话指标（用户满意度得分、会话点击次数和会话停留时间）时使用基线成本效益特征取得了更好的性能。此外，当通过改变搜索时间预期和用户满意度衰减率来运行模拟时，结果表明，用户倾向于期望在一分钟内完成搜索，并且一旦超过估计的期望点，就会以对数方式表现出快速的满意度衰减率。通过考虑用户的搜索时间预期并在未满足预期时测量他们的行为反应，我们可以进一步提高早期预测模型的性能并增强我们对用户行为模式的理解。 CCS 概念 • 信息系统→ 用户和交互式检索。
There is substantial evidence from behavioral economics and decision sciences demonstrating that in the context of decision-making under uncertainty, the carriers of value behind actions are gains and losses defined relative to a reference point (e.g. pre-action expectations), rather than the absolute final outcomes. Also, the capability of early predicting session-level search decisions and user experience is essential for developing reactive and proactive search recommendations. To address these research gaps, our study aims to 1) develop reference dependence features based on a series of simulated user expectations or reference points in first query segments of sessions, and 2) examine the extent to which we can enhance the performance of early predicting session behavior and user satisfaction by constructing and employing reference dependence features. Based on the experimental results on three datasets of varying types, we found that incorporating reference dependent features developed in first query segments into prediction models achieves better performance than using baseline cost-benefit features only in early predicting three key session metrics (user satisfaction score, session clicks, and session dwell time). Also, when running simulations by varying the search time expectation and rate of user satisfaction decay, the results demonstrate that users tended to expect to complete their search within a minute and showed a rapid rate of satisfaction decay in a logarithmic fashion once surpassing the estimated expectation points. By factoring in a user’s search time expectation and measuring their behavioral response once the expectation is not met, we can further improve the performance of early prediction models and enhance our understanding of users’ behavioral patterns. CCS CONCEPTS • Information systems → Users and interactive retrieval.