MDSE: Searching Multi-source Heterogeneous Material Data via Semantic Information Extraction

In this paper, we demonstrate MDSE, which provides effective information extraction and searching for multi-source heterogeneous materials data that are collected as XML documents. The major features of MDSE are: (1) We propose a transfer-learning-based approach to extract material information from non-textual material data, including images, videos, etc. (2) We present a heterogeneous-graph-based method to extract the semantic relationships among material data. (3) We build a search engine with both Google-like and tabular searching UIs to provide functional searching on integrated material data. After a brief introduction to the architecture and key technologies of MDSE, we present a case study to demonstrate the working process and the effectiveness of MDSE.