Metadata extraction and indexing for map search in web documents

ABSTRACT

In academic scientific articles, maps are widely used to provide the related geographic information and to give readers a visual understanding of the document content. As more digital documents containing maps become accessible on the Web, there is a growing demand for a Web search system to provide users with tools to retrieve documents based on the information available within a document's maps. In this paper, we design methods and algorithms to extract, identify, and index maps from academic and scientific documents in digital libraries. Experimental results show that our approach can accurately locate maps and significantly improve the retrieve quality for maps in digital documents.

REFERENCES

• 1: Google scholar. http://scholar.google.com/.
• 2: Pdflib text - text extraction toolkit. http://www.pdflib.com/products/tet/.
• 3: Ricardo A. Baeza-Yates , Berthier Ribeiro-Neto, Modern Information Retrieval, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, 1999
• 4: P. A. Devijver and J. Kittler. Pattern Recognition: A Statistical Approach. Prentice-Hall, London, 1982.
• 5: Thorsten Joachims, Making large-scale support vector machine learning practical, Advances in kernel methods: support vector learning, MIT Press, Cambridge, MA, 1999

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.4 INFORMATION SYSTEMS APPLICATIONS
      H.4.m Miscellaneous

Additional Classification:
  I. Computing Methodologies
  I.7 DOCUMENT AND TEXT PROCESSING
      I.7.0 General

General Terms:
Algorithms, Design, Experimentation

Keywords:
digital library, extraction, indexing, ranking function