Advertisement
Published in:
2006 | OriginalPaper | Chapter
Hybrid Method for Automated News Content Extraction from the Web
Authors : Yu Li, Xiaofeng Meng, Qing Li, Liping Wang
Published in: Web Information Systems – WISE 2006
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Web news content extraction is vital to improve news indexing and searching in nowadays search engines, especially for the news searching service. In this paper we study the Web news content extraction problem and propose an automated extraction algorithm for it. Our method is a hybrid one taking the advantage of both sequence matching and tree matching techniques. We propose
TSReC
, a variant of tag sequence representation suitable for both sequence matching and tree matching, along with an associated algorithm for automated Web news content extraction. By implementing a prototype system for Web news content extraction, the empirical evaluation is conducted and the result shows that our method is highly effective and efficient.