Ontology Learning for Chinese Information Organization and Knowledge Discovery in Ethnology and Anthropology

Jing Kong
2007 Data Science Journal  
This paper presents an ontology learning architecture that reflects the interaction between ontology learning and other applications such as ontology-engineering tools and information systems. Based on this architecture, we have developed a prototype system CHOL: a Chinese ontology learning tool. CHOL learns domain ontology from Chinese domain specific texts. On the one hand, it supports a semi-automatic domain ontology acquisition and dynamic maintenance, and on the other hand, it supports an
more » ... nd, it supports an auto-indexing and auto-classification of Chinese scholarly literature. CHOL has been applied in ethnology and anthropology for Chinese information organization and knowledge discovery. INTRODUCTION Since the 1990s, ontology has become a popular research topic studied by several artificial intelligence research communities. Ontologies, as shared conceptualizations for representing domain knowledge, are also becoming the key methods and tools in many fields, such as knowledge engineering, intelligent information integration, knowledge management, information retrieval, and the Semantic Web. Although ontology-engineering tools have matured over the last decade, manual ontology acquisition is a difficult, slow, time-consuming, tedious, and costly task that can easily result in a knowledge acquisition bottleneck. For this reason, it is necessary to develop methods and techniques that allow a reduction of the effort necessary for the ontology acquisition process, which is the goal of ontology learning. The term ontology learning was coined in 2000, at the first workshop on ontology learning held in conjunction with the 14th European Conference on Artificial Intelligence (ECAI2000). Gómez-Pérez defined ontology learning as the set of methods and techniques used for building an ontology from scratch or enriching or adapting an existing ontology in a semi-automatic fashion using several sources (Gómez-Pérez & Manzano-Macho, 2003) . Recently, there has been a surge of interest in studying ontology learning. In the past few years, many ontology learning tools such as
doi:10.2481/dsj.6.s500 fatcat:2wpsaolvkjenrhgxmbmjfoscl4