IEPAD: information extraction based on pattern discovery
Proceedings of the 10th international conference on World Wide Web
Data extraction and label assignment for web databases
WWW '03 Proceedings of the 12th international conference on World Wide Web
Extracting structured data from Web pages
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Testbed for information extraction from deep web
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
OLERA: Semisupervised Web-Data Extraction with Visual Support
IEEE Intelligent Systems
Web data extraction based on partial tree alignment
WWW '05 Proceedings of the 14th international conference on World Wide Web
ViPER: augmenting automatic information extraction with visual perceptions
Proceedings of the 14th ACM international conference on Information and knowledge management
A Survey of Web Information Extraction Systems
IEEE Transactions on Knowledge and Data Engineering
FiVaTech: Page-Level Web Data Extraction from Template Pages
IEEE Transactions on Knowledge and Data Engineering
Extracting data records from web using suffix tree
Proceedings of the ACM SIGKDD Workshop on Mining Data Semantics
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Web data extraction has been one of the keys for web content mining that tries to understand Web pages and discover valuable information from them. Most of the developed Web data extraction systems have used data (string/tree) alignment techniques. In this paper, we suggest a new algorithm for multiple string (peer matrix) alignment. Each row in the matrix represents one string of characters, where every character (symbol) corresponds to a subtree in the DOM tree of a web page. Two subtrees take the same symbol in the peer matrix if they are similar, where similarity can be measured using either structural, content, or visual information. Our algorithm is not a generalization of 2-strings alignment; it looks at multiple strings at the same time. Also, our algorithm considers the common problems in the field of Web data extraction: missing, multi-valued, multi-ordering, and disjunctive attributes. The experiments show a perfect alignment result with the matrices constructed from the nodes closed to the top (root) and an encourage result for the nodes closed to the leaves of the DOM trees of the test web pages.