摘要
[目的/意义]随着大语言模型应用的兴起,用户的信息获取渠道正在逐步转向新型的智能问答平台。这一转变产生的“多轮对话”序列数据可用作判断用户搜索效果的客观依据。[方法/过程]文章基于科研情境,探究用户信息搜寻行为中信息效用的构成原理。结合期望不一致理论,提出了信息效用测度模型,通过控制实验对不同用户认知背景下的信息效用价值进行测度。采用实验研究与定量数据分析相结合的方式,对用户与大语言模型的多轮交互流程进行了剖析,并采用累积效用值指标(Accumulate-Utility),探究用户信息搜寻过程中期望与实际体验间的差异给用户带来的效用变动,进一步验证了信息效用测度机制与信息效用模型框架的合理性。[结果/结论]信息效用模型框架较为合理地解释了用户信息搜寻的偏好情况、体验情况以及两者差异形成的最终效用水平,以及用户对不同属性任务的信息效用差异,进一步完善了分析信息搜寻效果的方法论。
[Purpose/significance]With the rise of generative large language models(LLMs)applications,users'information acquisition channels are gradually shifting toward intelligent Q&A platforms.This transformation generates“multi-turn dialogue”sequential data,which can serve as objective evidence for evaluating user search effectiveness.[Method/process]Based on a research context,this study explores the underlying principles of information utility in user information-seeking behavior.Integrating the Expectation-Disconfirmation Theory(EDT),we propose an information utility measurement model and conduct controlled experiments to assess the value of information utility across users with varying cognitive backgrounds.This study employs a combination of experimental research and quantitative data analysis to dissect multi-turn interactions between users and LLMs.Using the Accumulate-Utility metric,we examine how the gap between expectations and actual experiences influences utility fluctuations during information-seeking processes,thereby validating the proposed measurement mechanism.[Result/conclusion]The information utility framework effectively explains user preferences,experiential outcomes,and the resulting utility levels derived from their discrepancies.It also reveals variations in information utility across tasks with different attributes,further refining the methodology for analyzing information-seeking effectiveness.
作者
李颖
张彤
Li Ying;Zhang Tong(Business School,Nankai University,TianJin 300071)
出处
《情报理论与实践》
北大核心
2026年第1期88-95,共8页
Information Studies:Theory & Application
