Interactive Approach to Eliciting Users' Preference Using Comparisons

Jianfeng Zhang, Weihong Han, Yan Jia, Peng Zou
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引用次数: 0

Abstract

The complexity of today's networks and distributed systems makes the process of network monitoring difficult. The amount of data produced by many distributed security tools can be overwhelming. So it's very difficult and limited to get the most risky alert through manual process based on the huge network alerts with many attributes, such as asset, priority, reliability, risk, type et al. The common method used to rank the alerts is scoring function, the higher the score, the more risky of the alert. Our motivation is that many times user can not precisely specify the weights for the scoring function as their preference in order to produce the preferred order of results. In this paper, we propose a new interactive preference searching method to elicit user's preference. An extensive performance study using both synthetic and real datasets is reported to verify its effectiveness and efficiency.
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使用比较的交互式方法来引出用户偏好
当今网络和分布式系统的复杂性给网络监控过程带来了困难。许多分布式安全工具产生的数据量可能是压倒性的。因此,基于具有资产、优先级、可靠性、风险、类型等多种属性的庞大网络警报,通过人工流程获取风险最大的警报是非常困难和有限的。对警报进行排名的常用方法是评分函数,评分越高,警报的风险越大。我们的动机是,很多时候用户不能精确地指定评分函数的权重作为他们的偏好,以产生结果的首选顺序。本文提出了一种新的交互式偏好搜索方法来获取用户的偏好。使用合成和真实数据集进行了广泛的性能研究,以验证其有效性和效率。
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