关键词: 多源元数据, 决策树, 元数据判重, 元数据融合

Abstract: [Purpose/significance] Constructing a multi-source document metadata fusion model will help improve the overall quality of document metadata, promote metadata management and utilization in the resource discovery system, and optimize user resource discovery service experience. In view of the document metadata duplication judgment strategy proposed by the writers before, this paper optimizes the strategy from experience-oriented to automated, and improves the automation level in the whole process on the premise of guaranteeing the duplication judgment and fusion effect.[Method/process] The metadata items of different types of documents were different, and the metadata items of the same document from different sources were different, which will make the method of judging duplication different. An automatic multi-source document metadata fusion model based on the decision tree was proposed, which transformed a duplication judgment problem into a classification problem. This paper selected features according to feature similarity and constructed the decision tree, on this basis, it implemented metadata duplication judgment and fusion, and took different types of document resource metadata as examples to conduct experiments to verify the effectiveness of the strategy.[Result/conclusion] The results show that for the five document types of metadata, the accuracy of the duplication judgment strategy is more than 99%, and the recall rate is more than 98%. The overall effect is good. Judgment on the effect of the fusion strategy, the quality improvement ratios of the metadata items of patents, dissertations, journal papers, conference papers and books are 15.15%, 36.80%, 15.29%, 52.63% and 15.38% respectively, all of which have significant improvement.

Key words: multi-source metadata, the decision tree, metadata duplication judgment, metadata fusion