An Ontology-Based NLP Approach to Semantic Annotation of Annual Report

Author

Wang, Baohua ; Huang, Hejiang ; Wang, Xiaolong ; Chen, Wensheng

Author_Institution

Sch. of Comput. Sci. & Technol., Harbin Inst. of Technol., Shenzhen, China

Volume

1

fYear

2009

fDate

11-14 Dec. 2009

Firstpage

180

Lastpage

183

Abstract

Annual reports of Chinese securities companies have become the most significant and reliable source of information for domestic and foreign investors. Semantic annotation of them enhanced information retrieval and improved interoperability. In this paper we first review the major features of annual reports which are tagged PDF format, then propose a novel ontology-based NLP approach to semantic annotate them. The experimental results show in the paper state a good accuracy of our approach.

Keywords

information retrieval; natural language processing; ontologies (artificial intelligence); open systems; Chinese securities companies; domestic investor; enhanced information retrieval; foreign investors; interoperability; natural language approach; ontology-based NLP approach; semantic annotation; tagged PDF format; Computational intelligence; Computer science; Computer security; Educational institutions; Information resources; Information retrieval; Information security; Mathematics; Ontologies; XML; Annual Report; NLP; Tagged PDF documents; ontology; semantic annotation;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Security, 2009. CIS '09. International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-5411-2

Type

conf

DOI

10.1109/CIS.2009.269

Filename

5376652