An efficient pre-processing method to identify logical components from PDF documents
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
A practical method for compatibility evaluation of portable document formats
ACIIDS'13 Proceedings of the 5th Asian conference on Intelligent Information and Database Systems - Volume Part II
Towards generic framework for tabular data extraction and management in documents
Proceedings of the sixth workshop on Ph.D. students in information and knowledge management
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As the rapid growth of PDF documents, recognizing the document structure and components are useful for document storage, classification and retrieval. Table, a ubiquitous document component, becomes an important information source. Accurately detecting the table boundary plays a crucial role for many applications, e.g., the increasing demand on the table data search. Rather than converting PDFs to image or HTML and then processing with other techniques (e.g., OCR), extracting and analyzing texts from PDFs directly is easy and accurate. However, text extraction tools face a common problem: text sequence error. In this paper, we propose two algorithms to recover the sequence of extracted sparse lines, which improve the table content collection. The experimental results show the comparison of the performance of both algorithms, and demonstrate the effectiveness of text sequence recovering for the table boundary detection.