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A Novel Concept-Based Search for the Web of Data Using UMBEL and a Fuzzy Retrieval Model

机译:基于概念的新颖的UMBEL和模糊检索模型的数据网搜索

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摘要

As the size of Linked Open Data (LOD) increases, the search and access to the relevant LOD resources becomes more challenging. To overcome search difficulties, we propose a novel concept-based search mechanism for the Web of Data (WoD) based on UMBEL concept hierarchy and fuzzy-based retrieval model. The proposed search mechanism groups LOD resources with the same concepts to form categories, which is called concept lenses, for more efficient access to the WoD. To achieve concept-based search, we use UMBEL concept hierarchy for representing context of LOD resources. A semantic indexing model is applied for efficient representation of UMBEL concept descriptions and a novel fuzzy-based categorization algorithm is introduced for classification of LOD resources to UMBEL concepts. The proposed fuzzy-based model was evaluated on a particular benchmark (~10,000 mappings). The evaluation results show that we can achieve highly acceptable categorization accuracy and perform better than the vector space model.
机译:随着链接开放数据(LOD)大小的增加,对相关LOD资源的搜索和访问变得更具挑战性。为了克服搜索困难,我们基于UMBEL概念层次和基于模糊的检索模型,提出了一种新颖的基于概念的数据Web(WoD)搜索机制。所提出的搜索机制将具有相同概念的LOD资源分组以形成类别(称为概念镜头),以更有效地访问WoD。为了实现基于概念的搜索,我们使用UMBEL概念层次结构来表示LOD资源的上下文。应用语义索引模型来有效表示UMBEL概念描述,并引入了一种新颖的基于模糊的分类算法,将LOD资源分类为UMBEL概念。所提出的基于模糊的模型在特定基准(约10,000个映射)上进行了评估。评估结果表明,与矢量空间模型相比,我们可以实现高度可接受的分类精度,并且性能更好。

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