The Serialization of Heterogeneous Documents
Peter John Hampton, William Blackburn, Hui Wang
Citation: Position Papers of the 2015 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 6, pages 25–30 (2015)
Abstract. Tasks involving the analysis of natural language are typically conducted on a corpus or corpora of plain text. However, it is rare that a document is unstructured and freeform in its entirety. Documents such as corporate disclosures, medical journals and other knowledge rich archive contain structured and loosely-structured information that can be used in a variety of important text mining tasks. In this paper we propose a syntactical preprocessing architecture to serialize presentation- oriented documents to a machine readable format that aspires to preserve the document structure, contents and metadata. We introduce a hybrid pipeline architecture, discussing the various processes and the future research direction that could potentially lead to a holistic representation of heterogeneous documents.