Abstract

The Web mostly contains semi-structured information. It is, however, not easy to search and extract structural data hidden in a Web page. Current practices address this problem by (1) syntax analysis (i.e. HTML tags); or (2) wrappers or user-defined declarative languages. The former is only suitable for highly structured Web sites and the latter is time-consuming and offers low scalability. Wrappers could handle tens, but certainly not thousands, of information sources. In this paper, we present a novel information mining algorithm, namely KPS, over semi-structured information on the Web. KPS employs keywords, patterns and/or samples to mine the desired information. Experimental results show that KPS is more efficient than existing Web extracting methods.

Author Keywords: Information extraction; Information retrieval; Web query; Web databases

Article Outline

1. Introduction

1.1. Related work

2. Keyword-based mining

3. Pattern-based mining

4. Sample-based mining

4.1. The formal model

4.2. Pattern similarity

4.3. Style similarity

4.4. The algorithm

5. Experimental results

6. Conclusion and further works

Acknowledgements

Appendix

References

Vitae

^*E-mail: guan@cs.uregina.ca

¹E-mail: kfwong@se.cuhk.edu.hk