Semi-automatic Data Extraction from Tables
Н. А. Астраханцев, Денис Турдаков, Natalia Vassilieva · 2013
This paper describes a novel approach to automate extraction of useful information from tables and to record the knowledge procured in a structured data repository. The approach is based on modeling a behavior of an expert, who collects tabular data and maps them to a predefined relational schema. Experimental results demonstrate that the proposed approach predicts expert decisions with high accuracy and thus significantly minimizes the time required of an expert for data aggregation. 1