An Evaluation Study of the Automating Metadata Interoperability Model at Schema Level: A Case Study of the Digital Thai Lanna Archive
In digital library, large digital information is collected with some deviations of metadata structures. Various types of metadata standards and application profiles containing different sets of metadata elements are primarily concerned for information sharing and accessing among several digital collections. To allow information interoperability, librarians and domain experts traditionally take in a part of matching those metadata elements, which is a time consuming task. To alleviate the problem, a basic automating metadata interoperability model (AMI Model) is proposed for matching between two sets of simple level metadata elements by implementing a Crosswalk method based on the estimation of the semantic similarity values. The proposed model is evaluated on a case study of the Digital Thai Lanna archive based on the Mean Reciprocal Rank (MRR) performance measures. The result shows the proposed model accuracy is higher than the average accuracy at high acceptance level.
KeywordsAutomating Metadata Interoperability Crosswalk Semantic Similarity Digital Thai Lanna Archive Filtering Basic Global Thresholding
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