科研之友
微信
新浪微博
Facebook
分享链接
摘要
There are rich data resources residing in available materials websites, and most of these data resources are shown in the form of HTML tables. However, it is difficult to distinguish the attributes and values because of the semi-structured feature of HTML tables. Therefore, identifying attributes in HTML tables is the key issue for the information acquisition. In this paper, based on sibling comparison, a method for materials knowledge extraction from HTML tables is proposed, which consists of three steps: acquiring sibling tables, identifying table pattern and extracting table data. We show how to use F-measure to find the appropriate thresholds for matching of tables from materials websites when acquiring sibling tables. Further, we propose a strategy named FRFC (i.e. the First Row matching and First Column matching) to distinguish attributes and values, so that table pattern is identified. Moreover, the data from HTML tables is extracted based on their corresponding table patterns and mapped to a predefined schema, which will facilitate the population to materials ontology. The proposed approach is applicable to circumstances, where an attribute in the table may span multiple cells and matched attributes in sibling tables are more. We acquire desired accuracy (> 90%) through using FRFC for identifying table pattern. The time about extraction may not increase significantly with increasing number of documents and cells in tables, so our approach is effective to process a large number of documents. A prototype named MTES is developed and demonstrates the effectiveness of our proposed approach.
