Table understanding using a rule engine

• We propose an approach to table understanding using a rule engine.
• It is restricted by tasks of table analysis and interpretation.
• Spatial, style, and text information of tables is used for table understanding.
• Experimental results show the applicability of approach to a wide range of tables.
• The approach is designed for unstructured tabular data integration.

The paper discusses issues on the conversion of tabular data from unstructured to structured form. Particularly, we propose an approach to table understanding (i.e. recovering semantic relationships in a table), which is designed for unstructured tabular data integration. Our approach is based on using a rule engine. It is assumed that spatial, style (typographical), and natural language information can be used for table analysis and interpretation. The CELLS system based on the approach has been developed for integrating unstructured tabular data presented in Excel spreadsheet format. Experimental results show that the approach and system can be applied to a wide range of tables from statistical and financial reports.