Open Access
| Issue |
MATEC Web Conf.
Volume 139, 2017
2017 3rd International Conference on Mechanical, Electronic and Information Technology Engineering (ICMITE 2017)
|
|
|---|---|---|
| Article Number | 00118 | |
| Number of page(s) | 6 | |
| DOI | https://doi.org/10.1051/matecconf/201713900118 | |
| Published online | 05 December 2017 | |
- Hong, Haikun, et al. “Web Data Extraction Based on Tree Structure Analysis and Template Generation. ” International Conference on E-Product E-Service and E-Entertainment IEEE, 2010:1-5. E. [Google Scholar]
- Ma, Anxiang, et al. “Web Data Extraction Based on Structure Feature”. Applied Informatics and Communication. Springer Berlin Heidelberg, 2011. [Google Scholar]
- Hongyao Chang, “Research on The Body of Web Pages Based on Labelling Analysis”. Chongqing University, 2015. [Google Scholar]
- Wen Zhao “ Research on Web Page Structure Mining for Information Extraction”. Artificial Intelligence and Recognition Technology, 2008, 1(1):126-129. [Google Scholar]
- Jiang Liu, “A survey on sparse subspace clustering. ” Harbin Institute of Technology, 2012. [Google Scholar]
- Wang, Jiying, and F.H. Lochovsky. “Data extraction and label assignment for web databases. ” International Conference on World Wide Web ACM, 2003:187-196. [Google Scholar]
- Cormier, Michael “Computer vision-based analysis of web page structure for assistive interfaces. ” Web for All Conference ACM, 2016: 24. [Google Scholar]
- Chau, Michael, and H. Chen. “A machine learning approach to web page filtering using content and structure analysis. ” Decision Support Systems44. 2(2):482-494. [Google Scholar]
- Cesarini, Francesca, et al. “Page Classification for Meta-data Extraction from Digital Collections. ” International Conference on Database and Expert Systems Applications Springer-Verlag, 2015:82-91. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.