博物馆繁忙与空虚:游客人群对智能博物馆用户行为的影响

Seyyed Hadi Hashemi, J. Kamps, W. Hupperetz
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引用次数: 3

摘要

人们对智能环境中物联网(IoT)的集成越来越感兴趣,这为使用现场物理传感器日志了解用户的信息需求创造了机会。然而,物理环境产生了许多在用户信息交互中起作用的外部因素,从而在收集到的信息交互日志中产生了新的外部偏差。为了给智能环境下的用户提供有效的个性化体验,我们需要在行为用户模型中考虑到这些外部偏差。我们的总体目标是了解用户在现场的身体行为,以便提供个性化导游等在线和现场个性化服务。我们专注于文化遗产领域,收集现场用户参观博物馆的物理信息互动日志。这就引出了一个问题:如何在存在外部偏见的情况下理解用户的行为?我们的主要发现是,与繁忙的博物馆环境相比,用户在独处时的行为有所不同。具体而言,访客群体偏见对用户基于关注位置排名偏见的签到行为有相当大的影响。本研究旨在探讨如何准确地理解用户的现场物理行为,从而改进现有的现场行为用户模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Busy versus Empty Museums: Effects of Visitors' Crowd on Users' Behaviors in Smart Museums
There is a growing interests in integration of Internet of Things (IoT) in smart environments, which creates an opportunity to understand users' information needs using onsite physical sensor logs. However, the physical context creates numerous external factors that play a role in users' information interactions, thus creating new external biases in the collected information interaction logs. In order to provide an effective personalized experiences for users in smart environment, we need to take care of these external biases in the behavioral user models. Our general aim is to understand users' onsite physical behaviors for providing online and onsite personalized services like personalized tour guides. We focus on the cultural heritage domain and collect onsite users' physical information interaction logs of visits in a museum. This prompts the question: How to understand users' behavior in the existence of external biases? Our main finding is that users behave differently in their solitude in comparison to a busy museum situation. Specifically, visitors' crowd bias has a considerable effect on users' following position rank bias based check-in behavior. Our study investigates on understanding users' onsite physical behavior accurately, which can improve the state-of-the-art onsite behavioral user models.
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