Knowledge-Based Approaches to Query Expansion in Information Retrieval
AI '96 Proceedings of the 11th Biennial Conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
iO2 - An Algorithmic Method for Building Inheritance Graphs in Object Database Design
ER '96 Proceedings of the 15th International Conference on Conceptual Modeling
International Journal of Multimedia Data Engineering & Management
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In this study we present a novel hybrid system by developing a formal method of automatic ontology generation for web-based audio signal processing applications. An ontology is seen as a knowledge management structure that represents domain knowledge in a machine interpretable format. It describes concepts and relationships within a particular domain, in our case, the domain of musical instruments. The different tasks of ontology engineering including manual annotation, hierarchical structuring and organisation of data can be laborious and challenging. For these reasons, we investigate how the process of creating ontologies can be made less dependent on human supervision by exploring concept analysis techniques in a Semantic Web environment. Only a few methods have been proposed for automatic ontology generation. These are mostly based on statistical methods (e.g., frequency of semantic tags) that generate the taxonomy structure of ontologies as in the studies from Bodner and Songs [1]. The algorithms that have been used for automatic ontology generation are Hierarchical Agglomerative Clustering (HAC), Bi-Section K-Means [2], and Formal Concept Analysis (FCM). Formal Concept Analysis is a well established technique for identifying groups of elements with common sets of properties. Formal Concept Analysis has been used in many software engineering topics such as the identication of ob jects in legacy code, or the identication and restructuring of schema in ob ject-oriented databases [5]. These works are important since ontologies provide the basis for information and database systems [6].