Relevance weighting of search terms
Document retrieval systems
A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
Mining generalized association rules
Future Generation Computer Systems - Special double issue on data mining
SPADE: an efficient algorithm for mining frequent sequences
Machine Learning
Using text processing techniques to automatically enrich a domain ontology
Proceedings of the international conference on Formal Ontology in Information Systems - Volume 2001
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
The PSP Approach for Mining Sequential Patterns
PKDD '98 Proceedings of the Second European Symposium on Principles of Data Mining and Knowledge Discovery
Centroid-Based Document Classification: Analysis and Experimental Results
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
EKAW '00 Proceedings of the 12th European Workshop on Knowledge Acquisition, Modeling and Management
Automatic Acquisition of Hyponyms
Automatic Acquisition of Hyponyms
Pre-Processing Time Constraints for Efficiently Mining Generalized Sequential Patterns
TIME '04 Proceedings of the 11th International Symposium on Temporal Representation and Reasoning
Sequential patterns for text categorization
Intelligent Data Analysis
Extended Time Constraints for Sequence Mining
TIME '07 Proceedings of the 14th International Symposium on Temporal Representation and Reasoning
Web Semantics: Science, Services and Agents on the World Wide Web
Proxemic conceptual network based on ontology enrichment for representing documents in IR
EKAW'12 Proceedings of the 18th international conference on Knowledge Engineering and Knowledge Management
A Pattern Language for Knowledge Discovery in a Semantic Web context
International Journal of Information Technology and Web Engineering
| Hi-index | 0.00 |
Ontologies are known as a quality and functional model, allowing meta data representation and reasoning. However, their maintenance plays a crucial role as ontologies may be misleading if they are not up to date. Currently, this work is done manually, and raises the problem of expert subjectivity. Therefore, some works have developed maintenance tools but none has allowed a precise identification of the relations that could link concepts. In this paper, we propose a new fully generic approach combining sequential patterns extraction and equivalence classes. Our method allows to identify terms from textual documents and to define labelized association rules from sequential patterns according to relevance and neighborhood measures. Moreover, this process proposes the placement of the found elements refined by the use of equivalence classes. Results of various experiments on real data highlight the relevance of our proposal.