- Evaluating intuitiveness of vertical-aware click models
- SIGIR '14: 37th international ACM SIGIR conference on Research and development in information retrieval
- Book/source title
- SIGIR '14: proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval: July 6-11 2014, Gold Coast, Queensland, Australia
- Pages (from-to)
- New York, NY: ACM
- Document type
- Conference contribution
- Faculty of Science (FNWI)
- Informatics Institute (IVI)
Modeling user behavior on a search engine result page is important for understanding the users and supporting simulation experiments. As result pages become more complex, click models evolve as well in order to capture additional aspects of user behavior in response to new forms of result presentation.
We propose a method for evaluating the intuitiveness of vertical-aware click models, namely the ability of a click model to capture key aspects of aggregated result pages, such as vertical selection, item selection, result presentation and vertical diversity. This method allows us to isolate model components and therefore gives a multi-faceted view on a model's performance. We argue that our method can be used in conjunction with traditional click model evaluation metrics such as log-likelihood or perplexity. In order to demonstrate the power of our method in situations where result pages can contain more than one type of vertical(e.g., Image and News) we extend the previously studied Federated Click Model such that it models user clicks on such pages. Our evaluation method yields non-trivial yet interpretable conclusions about the intuitiveness of click models, highlighting their strengths and weaknesses.
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- Short paper
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