Automatic web news extraction using tree edit distance

By D. C. Reis, P. B. Golgher, A. D. Silva, Alberto H. F. Laender. The Web Conference, 2004

393 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems

View Paper: https://www.semanticscholar.org/paper/83cc20d078920efa6cc3876a83065beddb592474

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Benjamin Van Durme
2. Peter Clark
3. Yejin Choi
4. Mohit Bansal
5. B. Liu
6. Chris Callison-Burch
7. Yanhong Zhai
8. Ashish Sabharwal

In Information Systems

1. B. Liu
2. Emilio Ferrara
3. Pasquale De Meo
4. Robert Baumgartner
5. Giacomo Fiumara
6. Yanhong Zhai
7. Chris Callison-Burch
8. Xuchen Yao

Citations in the corpus

• Answer Extraction as Sequence Tagging with Tree Edit Distance (2013, background): “Tree Edit Distance ( § 2.1) models have been shown effective in a variety of applications, including textual entailment, paraphrase identification, answer ranking and information retrieval (Reis et al., 2004; Kouylekov and Magnini, 2005; Heilman and Smith, 2010; Augsten et al., 2010).”
• Web data extraction based on partial tree alignment (2005, methodology): “Finally, tree matching has been used for finding the main contents in news pages in [27].”
• Web Data Extraction, Applications and Techniques: A Survey (2012, background): “The worst case time complexity of the approach of [102] is still OðnodesðAÞ nodesðBÞÞ but, as shown by the authors, it works much faster because only restricted top-down mappings are managed.”