SimIIR 2.0框架:用户类型、基于马尔可夫模型的交互模拟和高级查询生成

Proceedings of the 31st ACM International Conference on Information & Knowledge Management Pub Date : 2022-10-17 DOI:10.1145/3511808.3557711

Saber Zerhoudi, S. Günther, Kim Plassmeier, Timo Borst, C. Seifert, Matthias Hagen, M. Granitzer

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引用次数: 4

摘要

模拟用户检索系统交互使研究与控制用户行为。为此，SimIIR框架提供了静态的、基于规则的方法。我们提供了一个扩展的SimIIR 2.0版本，其中包含了用于基于特定用户类型的马尔可夫模型的动态交互和更现实的查询生成的新组件。灵活的模块化确保了SimIIR 2.0框架可以作为一个平台来实现、组合和运行越来越多的提议的搜索行为和查询模拟思想。

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The SimIIR 2.0 Framework: User Types, Markov Model-Based Interaction Simulation, and Advanced Query Generation

Simulated user retrieval system interactions enable studies with controlled user behavior. To this end, the SimIIR framework offers static, rule-based methods. We present an extended SimIIR 2.0 version with new components for dynamic user type-specific Markov model-based interactions and more realistic query generation. A flexible modularization ensures that the SimIIR 2.0 framework can serve as a platform to implement, combine, and run the growing number of proposed search behavior and query simulation ideas.

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Proceedings of the 31st ACM International Conference on Information & Knowledge Management

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