A survey of ontology-based web annotation

Heterogeneity and a lack of central control over the organization of Web information have led to great difficulties in processing them automatically. To overcome the difficulties, one attempts to add metadata to Web pages and this is known as Web Annotation. Ontology-based Web Annotation is a recent but promising area which enhances conventional Web Annotations by incorporating ontology with pre-defined semantic structures. The resulting annotations are useful not only for navigating Web information from diverse sources but also for improving information retrieval and classification. In this paper, we survey the different Ontology-based Web annotation methods in order to provide an organized view on the existing state-of-the-art, to identify potential areas of research, and to discuss promising ways of enhancing Ontology-based Web Annotation.

[1]  Line Eikvil,et al.  Information Extraction from World Wide Web - A Survey , 1999 .

[3]  Mark Craven,et al.  First-Order Learning for Web Mining , 1998, ECML.

[4]  Raymond J. Mooney,et al.  Relational Learning of Pattern-Match Rules for Information Extraction , 1999, CoNLL.

[5]  Yoram Singer,et al.  Context-sensitive learning methods for text categorization , 1996, SIGIR '96.

[6]  Dieter Fensel,et al.  Ontobroker: Ontology Based Access to Distributed and Semi-Structured Information , 1999, DS-8.

[7]  Nicholas Kushmerick,et al.  Wrapper induction: Efficiency and expressiveness , 2000, Artif. Intell..

[8]  Craig A. Knoblock,et al.  A hierarchical approach to wrapper induction , 1999, AGENTS '99.

[9]  Stephen Soderland,et al.  Learning Information Extraction Rules for Semi-Structured and Free Text , 1999, Machine Learning.

[10]  Thomas G. Dietterich.  What is machine learning? , 2020, Archives of Disease in Childhood.

[11]  Dayne Freitag,et al.  Information Extraction from HTML: Application of a General Machine Learning Approach , 1998, AAAI/IAAI.

[12]  Steffen Staab,et al.  CREAM: creating relational metadata with a component-based, ontology-driven annotation framework , 2001, K-CAP '01.

[13]  Mark Craven,et al.  Relational Learning with Statistical Predicate Invention: Better Models for Hypertext , 2001, Machine Learning.

[14]  Enrico Motta,et al.  Knowledge Extraction by Using an Ontology Based Annotation Tool , 2001, Semannot@K-CAP 2001.

[15]  Steffen Staab,et al.  From Manual to Semi-Automatic Semantic Annotation: About Ontology-Based Text Annotation Tools , 2000, SAIC@COLING.

[16]  Steffen Staab,et al.  Creating Metadata for the Semantic Web — An Annotation Environment and the Human Factor , 2000 .

[17]  Fabrizio Sebastiani,et al.  Machine learning in automated text categorization , 2001, CSUR.

[18]  Ion Muslea,et al.  Extraction Patterns for Information Extraction Tasks: A Survey , 1999 .

[19]  Steffen Staab,et al.  An annotation framework for the semantic web , 2001 .

[20]  Steffen Staab,et al.  Authoring and annotation of web pages in CREAM , 2002, WWW '02.

[21]  Michael Gertz,et al.  Web data indexing through external semantic-carrying annotations , 2001, Proceedings Eleventh International Workshop on Research Issues in Data Engineering. Document Management for Data Intensive Business and Scientific Applications. RIDE 2001.

[22]  James A. Hendler,et al.  Towards the semantic web: knowledge representation in a dynamic, distributed environment , 2001 .

[23]  Tom M. Mitchell,et al.  Learning to construct knowledge bases from the World Wide Web , 2000, Artif. Intell..