交互式信息系统满意度建模地形适应网络 (Brain Topography Adaptive Network for Satisfaction Modeling in Interactive Information Access System)

With the growth of information on the Web, most users heavily rely on information access systems (e.g., search engines, recommender systems, etc.) in their daily lives. During this procedure, modeling users' satisfaction status plays an essential part in improving their experiences with the systems. In this paper, we aim to explore the benefits of using Electroencephalography (EEG) signals for satisfaction modeling in interactive information access system design. Different from existing EEG classification tasks, the arisen of satisfaction involves multiple brain functions, such as arousal, prototypicality, and appraisals, which are related to different brain topographical areas. Thus modeling user satisfaction raises great challenges to existing solutions. To address this challenge, we propose BTA, a Brain Topography Adaptive network with a multi-centrality encoding module and a spatial attention mechanism module to capture cognitive connectivities in different spatial distances. We explore the effectiveness of BTA for satisfaction modeling in two popular information access scenarios, i.e., search and recommendation. Extensive experiments on two real-world datasets verify the effectiveness of introducing brain topography adaptive strategy in satisfaction modeling. Furthermore, we also conduct search result re-ranking task and video rating prediction task based on the satisfaction inferred from brain signals on search and recommendation scenarios, respectively. Experimental results show that brain signals extracted with BTA help improve the performance of interactive information access systems significantly.

翻译：随着网上信息的增长,大多数用户在日常生活中高度依赖信息访问系统(例如搜索引擎、建议系统等)。在这一过程中,模拟用户的满意度状况在改进系统经验方面起着重要作用。在本文件中,我们的目的是探讨在交互式信息访问系统设计中利用电子脑phalphalogy(EEEG)信号进行满意度建模以建立互动信息访问系统设计中的满意度模型的好处。与现有的电子EEG分类任务不同,满意度的产生涉及多种大脑功能,如与不同脑地形领域有关的激励、超典型和评估。因此,模拟用户满意度给现有解决方案带来了巨大挑战。为了应对这一挑战,我们建议BTA、带有多中心编码模块的脑地形适应性网络和一个空间关注机制模块,以捕捉不同空间距离的认知性连接。我们探索BTA在两种流行信息访问假设情景(即搜索和建议)中的满意度建模效果。在两种现实世界数据集上进行广泛的实验,以核实在满意度、感测得战略的有效性。此外,我们还提议BTA型图像搜索结果,根据测试结果,分别根据满意度、测试、测试、测试、测试、测试、测试、测试、测试、结果、测试、测试、测试、测试、测试、测试、测试、测试、测试、测试、结果、测试、测试、结果、测试、测试、测试、测试、测试、结果、结果、结果、测试、测试、结果、测试、测试、测试、测试、结果、结果、测试、测试、结果、结果、测试、测试、测试、测试、测试、测试、结果、结果、测试、测试、测试、结果、结果、测试、测试、测试、测试、结果、测试、测试、测试、测试、结果、结果、结果、测试、测试、测试、测试、测试、测试、测试、测试、测试、测试、测试、测试、测试、结果、测试、测试、测试、测试、测试、测试、测试、结果、结果、测试、测试、测试、测试、测试、测试、测试、测试、结果、结果、测试、测试、测试、结果、结果、结果、测试、测试、测试、测试、测试、测试、结果、结果、测试、结果、结果、结果、结果、结果、结果、结果、测试、测试、测试、测试、测试、测试、测试、测试、测试、测试、测试、测试、