The HCMUS team participated in the RCIR (Reading Comprehension in Information Retrieval) task of the NTCIR-16. The RCIR task aims to evaluate different techniques to rank text content with useful eye tracking information. In this paper, we present our methods to solve the problem of the Comprehension-evaluation Task (CET). We follow the feature processing and engineering strategy, and we adopt different techniques, such as BERT, PCA, and AutoML, to generate output results for this task. Our best solution achieves the Spearmans correlation coefficient of 0.50846.
Liu et al. (Tue,) studied this question.
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