The nature of statistical learning theory
The nature of statistical learning theory
Inductive learning algorithms and representations for text categorization
Proceedings of the seventh international conference on Information and knowledge management
A re-examination of text categorization methods
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Hierarchical classification of Web content
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Proceedings of the 10th international conference on World Wide Web
Learning to map between ontologies on the semantic web
Proceedings of the 11th international conference on World Wide Web
Machine Learning
Modern Information Retrieval
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Transductive Inference for Text Classification using Support Vector Machines
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Using Taxonomy, Discriminants, and Signatures for Navigating in Text Databases
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Facilitating the Exchange of Explicit Knowledge through Ontology Mappings
Proceedings of the Fourteenth International Florida Artificial Intelligence Research Society Conference
PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
The Chimaera Ontology Environment
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Ontologies: A Silver Bullet for Knowledge Management and Electronic Commerce
Ontologies: A Silver Bullet for Knowledge Management and Electronic Commerce
FCA-MERGE: bottom-up merging of ontologies
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Hierarchical Dirichlet model for document classification
ICML '05 Proceedings of the 22nd international conference on Machine learning
Using Bayesian decision for ontology mapping
Web Semantics: Science, Services and Agents on the World Wide Web
Web Directory Integration Using Conditional Random Fields
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
An integrated system for building enterprise taxonomies
Information Retrieval
Unification of sorts among local ontologies for semantic web applications
AIKED'05 Proceedings of the 4th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering Data Bases
Information retrieval on bug locations by learning co-located bug report clusters
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Web taxonomy integration with hierarchical shrinkage algorithm and fine-grained relations
Expert Systems with Applications: An International Journal
AIRS'08 Proceedings of the 4th Asia information retrieval conference on Information retrieval technology
International Journal of Knowledge and Web Intelligence
Collective taxonomizing: A collaborative approach to organizing document repositories
Decision Support Systems
Rule extraction from support vector machines: A review
Neurocomputing
A Comprehensive Study of Features and Algorithms for URL-Based Topic Classification
ACM Transactions on the Web (TWEB)
Transactions on computational collective intelligence V
Regularization for unsupervised classification on taxonomies
ISMIS'06 Proceedings of the 16th international conference on Foundations of Intelligent Systems
CMSA: a method for construction and maintenance of semantic annotations
ISPA'05 Proceedings of the 2005 international conference on Parallel and Distributed Processing and Applications
AIRS'05 Proceedings of the Second Asia conference on Asia Information Retrieval Technology
An iterative approach for web catalog integration with support vector machines
AIRS'05 Proceedings of the Second Asia conference on Asia Information Retrieval Technology
Learning to integrate web catalogs with conceptual relationships in hierarchical thesaurus
AIRS'06 Proceedings of the Third Asia conference on Information Retrieval Technology
A cross-lingual framework for web news taxonomy integration
AIRS'06 Proceedings of the Third Asia conference on Information Retrieval Technology
A TSVM-Based minutiae matching approach for fingerprint verification
IWBRS'05 Proceedings of the 2005 international conference on Advances in Biometric Person Authentication
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We address the problem of integrating objects from a source taxonomy into a master taxonomy. This problem is not only currently pervasive on the web, but also important to the emerging semantic web. A straightforward approach to automating this process would be to train a classifier for each category in the master taxonomy, and then classify objects from the source taxonomy into these categories. In this paper we attempt to use a powerful classification method, Support Vector Machine (SVM), to attack this problem. Our key insight is that the availability of the source taxonomy data could be helpful to build better classifiers in this scenario, therefore it would be beneficial to do transductive learning rather than inductive learning, i.e., learning to optimize classification performance on a particular set of test examples. Noticing that the categorizations of the master and source taxonomies often have some semantic overlap, we propose a method, Cluster Shrinkage (CS), to further enhance the classification by exploiting such implicit knowledge. Our experiments with real-world web data show substantial improvements in the performance of taxonomy integration.