ChengXiang Zhai
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
ChengXiang Zhai has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Bruce R. Schatz
Department of Computer Science, Institute for Genomic Biology, University of Illinois at Urbana-Champaign, IL 61801, United States
1 shared publication - Kevin Chen-Chuan Chang
Computer Science Department, University of Illinois at Urbana-Champaign
1 shared publication - Qiaozhu Mei
Department of Computer Science, Institute for Genomic Biology, University of Illinois at Urbana-Champaign, IL 61801, United States
1 shared publication - Shui-Lung Chuang
Computer Science Department, University of Illinois at Urbana-Champaign
1 shared publication - Xin He
Department of Computer Science, Institute for Genomic Biology, University of Illinois at Urbana-Champaign, IL 61801, United States
1 shared publication - Xu Ling
Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
1 shared publication
Latest Publications
- 30 November 2007
- Published by Elsevier in Information Processing & Management
- Vol. 43 (6) , 1777-1791
Generating gene summaries from biomedical literature: A study of semi-structured summarization
- 30 November 2007
- Published by Elsevier in Information Processing & Management
- Vol. 43 (6) , 1777-1791
Generating gene summaries from biomedical literature: A study of semi-structured summarization
- 1 January 2007
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 1261-1262
Collaborative Wrapping: A Turbo Framework for Web Data Extraction
To access data sources on the Web, a crucial step is wrapping, which translates query responses, rendered in textual HTML, back into their relational form. Traditionally, this problem has been addressed with syntax-based approaches for a single source. However, as online databases multiply, we often need to wrap multiple sources, in particular for domain-based integration. Observing that sources in the same domain usually share common fields, we propose a novel wrapping concept - collaborative wrapping - where multiple sources are extracted concurrently with content-based synchronization to produce consentaneous extractions. Toward this concept, recognizing wrapping as a communication process, we develop the turbo wrapper, upon the insight of turbo codes - a multi-code decoding scheme in information theory. Our experiment shows that the turbo wrapper consistently outperforms baseline single-source methods, is robust, and does benefit from extended scales of source collaboration.
- 1 January 2007
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 1261-1262
Collaborative Wrapping: A Turbo Framework for Web Data Extraction
To access data sources on the Web, a crucial step is wrapping, which translates query responses, rendered in textual HTML, back into their relational form. Traditionally, this problem has been addressed with syntax-based approaches for a single source. However, as online databases multiply, we often need to wrap multiple sources, in particular for domain-based integration. Observing that sources in the same domain usually share common fields, we propose a novel wrapping concept - collaborative wrapping - where multiple sources are extracted concurrently with content-based synchronization to produce consentaneous extractions. Toward this concept, recognizing wrapping as a communication process, we develop the turbo wrapper, upon the insight of turbo codes - a multi-code decoding scheme in information theory. Our experiment shows that the turbo wrapper consistently outperforms baseline single-source methods, is robust, and does benefit from extended scales of source collaboration.