open access

https://hdl.handle.net/2115/68486

A Language-Independent Ontology Construction Method Using Tagged Images in Folksonomy

英語

tag refinement

2018

IEEE

IEEE Access

6

2930-2942

This paper presents a language-independent ontology (LION) construction method that uses tagged images in an image folksonomy. Existing multilingual frameworks that construct an ontology deal with concepts translated on the basis of parallel corpora, which are not always available; however, the proposed method enables LION construction without parallel corpora by using visual features extracted from tagged images as the alternative. In the proposed method, visual similarities in tagged images are leveraged to aggregate synonymous concepts across languages. The aggregated concepts take on intrinsic semantics of themselves, while they also hold distinct characteristics in different languages. Then relationships between concepts are extracted on the basis of visual and textual features. The proposed method constructs a LION whose nodes and edges correspond to the aggregated concepts and relationships between them, respectively. The LION enables successful image retrieval across languages since each of the aggregated concepts can be referred to in different languages. Consequently, the proposed method removes the language barriers by providing an easy way to access a broader range of tagged images for users in the folksonomy, regardless of the language they use.

学術雑誌論文

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2169-3536