Abstract：This paper presents a new approach to Ontology learning in the domain of information science. A combination of Formal Concept Analysis (FCA) and association rules is used to facilitate Ontology construction from unstructured text. This approach acquires key concepts from documents by using a seeding and expansion mechanism; formulates (key concept by document) context for concept lattice construction, and bootstraps the learning of domain-specific concept hierarchies using FCA; extracts the relationships between the concepts via association rules. To evaluate the quality of the learned Ontology, a comparison with “Golden Standard” is undertaken, and the evaluation results illustrate that it can reach high domain coverage and identify some implicit relations between concepts. It is concluded that the proposed method is practical and useful to support the process of building domain Ontology.
刘萍, 胡月红. 基于FCA和关联规则的情报学本体构建[J]. 现代图书情报技术, 2012, 28(2): 34-40.
Liu Ping, Hu Yuehong. Development of Domain Ontology in Information Science Based on FCA and Association Rules. New Technology of Library and Information Service, DOI：10.11925/infotech.1003-3513.2012.02.06.
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