Building intelligent web applications using lightweight wrappers
Data & Knowledge Engineering - Special issue on heterogeneous information resources need semantic access
A brief survey of web data extraction tools
ACM SIGMOD Record
Hierarchical Wrapper Induction for Semistructured Information Sources
Autonomous Agents and Multi-Agent Systems
ICDT '99 Proceedings of the 7th International Conference on Database Theory
Visual Web Information Extraction with Lixto
Proceedings of the 27th International Conference on Very Large Data Bases
RoadRunner: Towards Automatic Data Extraction from Large Web Sites
Proceedings of the 27th International Conference on Very Large Data Bases
Learning the Common Structure of Data
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Data extraction and label assignment for web databases
WWW '03 Proceedings of the 12th international conference on World Wide Web
XWRAP: An XML-Enabled Wrapper Construction System for Web Information Sources
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Extracting structured data from Web pages
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
A Supervised Visual Wrapper Generator for Web-Data Extraction
COMPSAC '03 Proceedings of the 27th Annual International Conference on Computer Software and Applications
Schema-guided wrapper maintenance for web-data extraction
WIDM '03 Proceedings of the 5th ACM international workshop on Web information and data management
A two-phase rule generation and optimization approach for wrapper generation
ADC '06 Proceedings of the 17th Australasian Database Conference - Volume 49
On-line web database integration
Proceedings of the International Conference on Management of Emergent Digital EcoSystems
| Hi-index | 0.00 |
Extracting data from web pages using wrappers is a fundamental problem arising in a large variety of applications of vast practical interests. In this paper, we propose a novel technique to the problem of differentiating roles of data items from Web pages, which is one of the key problems in our automatic extraction approach. The problem is resolved at various levels: semantic blocks, sections and data items, and several approaches are proposed to effectively identify the mapping between data items having the same role. Intensive experiments on real web sites show that the proposed technique can effectively help extracting desired data with high accuracies in most of the cases.