Xiangmin Zhang
Nicholas Belkin
ABSTRACT
This study uses regression modeling to predict a user's domain knowledge level (DK) from implicit evidence provided by certain search behaviors. A user study (n=35) with recall-oriented search tasks in the genomic domain was conducted. A number of regression models of a person's DK, were generated using different behavior variable selection methods. The best model highlights three behavior variables as DK predictors: the number of documents saved, the average query length, and the average ranking position of documents opened. The model is validated using the split sampling method. Limitations and future research directions are discussed.
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Index Terms
- Predicting users' domain knowledge from search behaviors
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