Migrating data-intensive web sites into the Semantic Web
Proceedings of the 2002 ACM symposium on Applied computing
EKAW '99 Proceedings of the 11th European Workshop on Knowledge Acquisition, Modeling and Management
Exploiting Structure for Intelligent Web Search
HICSS '01 Proceedings of the 34th Annual Hawaii International Conference on System Sciences ( HICSS-34)-Volume 4 - Volume 4
Web-scale information extraction in knowitall: (preliminary results)
Proceedings of the 13th international conference on World Wide Web
Identification of relevant terms to support the construction of domain ontologies
HLTKM '01 Proceedings of the workshop on Human Language Technology and Knowledge Management - Volume 2001
A methodology for clustering XML documents by structure
Information Systems
Discovering Groups of Sibling Terms from Web Documents with XTREEM-SG
Journal on Data Semantics XI
The XTREEM Methods for Ontology Learning from Web Documents
Proceedings of the 2008 conference on Ontology Learning and Population: Bridging the Gap between Text and Knowledge
Discovering semantic sibling associations from web documents with XTREEM-SP
DaWaK'06 Proceedings of the 8th international conference on Data Warehousing and Knowledge Discovery
Discovering semantic sibling groups from web documents with XTREEM-SG
EKAW'06 Proceedings of the 15th international conference on Managing Knowledge in a World of Networks
Learning of semantic sibling group hierarchies - K-means vs. bi-secting-K-means
DaWaK'07 Proceedings of the 9th international conference on Data Warehousing and Knowledge Discovery
Domain relevance on term weighting
NLDB'07 Proceedings of the 12th international conference on Applications of Natural Language to Information Systems
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The Semantic Web needs ontologies as an integral component. Current methods for learning and enhancing ontologies, need to be further improved to overcome the knowledge acquisition bottleneck. The identification of concepts and relations with only minimal user interaction is still a challenging objective. Current approaches performed to extract semantics often use association rules or clustering upon regular flat text. In this paper we describe an approach on extracting semantics from Web Document collections which takes advantage of the semi structured content within XHTML (an XML dialect which can be obtained from traditional HTML documents) Web Documents. The XTREEM (Xhtml TREE Mining) method uses structural information, the mark-up in Web content, as indicators of term boundaries and for co-hyponymy relations.