Automatic semantic modeling of structured data sources with cross-modal retrieval

Ruiqing Xu, Wolfgang Mayer, Hailong Chu, Yitao Zhang, Hong-Yu Zhang, Yulong Wang, Youfa Liu, Zaiwen Feng

Abstract: Highlights•A novel supervised table-graph cross-modal retrieval model for automatic semantic modeling.•An explainable representation learning method combining graph representation learning with an incremental search algorithm.•An attention mechanism and iterative matching method to learn fine-grained semantic matches between different modalities.•The experimental results using two different semantic labelers validate the effectiveness and robustness of our method.•The cross-modal retrieval-based method outperforms the previous best method in terms of precision, recall, and f1-score.