Generating finite-state transducers for semi-structured data extraction from the Web
Information Systems - Special issue on semistructured data
Building intelligent web applications using lightweight wrappers
Data & Knowledge Engineering - Special issue on heterogeneous information resources need semantic access
Hierarchical Wrapper Induction for Semistructured Information Sources
Autonomous Agents and Multi-Agent Systems
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
Mining data records in Web pages
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
The Lixto data extraction project: back and forth between theory and practice
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Fully automatic wrapper generation for search engines
WWW '05 Proceedings of the 14th international conference on World Wide Web
Web data extraction based on partial tree alignment
WWW '05 Proceedings of the 14th international conference on World Wide Web
Extracting semantic structure of web documents using content and visual information
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
IEEE Transactions on Knowledge and Data Engineering
ViPER: augmenting automatic information extraction with visual perceptions
Proceedings of the 14th ACM international conference on Information and knowledge management
Structured Data Extraction from the Web Based on Partial Tree Alignment
IEEE Transactions on Knowledge and Data Engineering
Scalable web data extraction for online market intelligence
Proceedings of the VLDB Endowment
ViDE: A Vision-Based Approach for Deep Web Data Extraction
IEEE Transactions on Knowledge and Data Engineering
Extracting content structure for web pages based on visual representation
APWeb'03 Proceedings of the 5th Asia-Pacific web conference on Web technologies and applications
SXPath: extending XPath towards spatial querying on web documents
Proceedings of the VLDB Endowment
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A large part of information available on the Web is hidden to conventional research engines because Web pages containing such information are dynamically generated as answers to query submitted by search form filled in by keywords. Such pages are referred as Deep Web pages and contain huge amount of relevant information for different application domain. For these reasons there is a constant high interest in efficiently extracting data from Deep Web data sources. In this paper we present a spatial instance learning method from Deep Web pages that exploits both the spatial arrangement and the visual features of data records and data items/fields produced by layout engines of web browsers. The proposed method is independent from the DeepWeb pages encoding and from the presentation layout of data records. Furthermore, it allows for recognizing data records in Deep Web pages having multiple data regions. In the paper the effectiveness of the proposed method is proven by experiments carried out on a dataset of 100 Web pages randomly selected from most known Deep Web sites. Results obtained by using the proposed method show that the method has a very high precision and recall and that system works much better than MDR and ViNTS approaches applied to the same dataset.