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Transformation Rules for Decomposing Heterogeneous Data Into Triples

المصدر: مجلة جامعة الملك سعود - علوم الحاسب والمعلومات
الناشر: جامعة الملك سعود
المؤلف الرئيسي: Singh, Mrityunjay (Author)
مؤلفين آخرين: Jain, S. K. (Co-Author)
المجلد/العدد: مج27, ع2
محكمة: نعم
الدولة: السعودية
التاريخ الميلادي: 2015
الصفحات: 181 - 192
DOI: 10.33948/0584-027-002-009
ISSN: 1319-1578
رقم MD: 973579
نوع المحتوى: بحوث ومقالات
اللغة: الإنجليزية
قواعد المعلومات: science
مواضيع:
كلمات المؤلف المفتاحية:
Information Integration | Dataspace System | Triple Model | Heterogeneity | Transformation Rules Set | Data Modeling
رابط المحتوى:
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المستخلص: In order to fulfill the vision of a data space system, it requires a flexible, powerful and versatile data model that is able to represent a highly heterogeneous mix of data such as databases, web pages, XML, deep web, and files. In literature, the triple model was found a suitable candidate for a data space system, and able to represent structured, semi structured and unstructured data into a single model. A triple model is based on the decomposition theory, and represents variety of data into a collection of triples. In this paper, we have proposed a decomposition algorithm for expressing various heterogeneous data models into the triple model. This algorithm is based on the decomposition theory of the triple model. By applying the decomposition algorithm, we have proposed a set of transformation rules for the existing data models. The transformation rules have been categorized for structured, semi structured, and unstructured data models. These rules are able to decompose most of the existing data models into the triple model. We have empirically verified the algorithm as well as the transformation rules on different data sets having different data models.

ISSN: 1319-1578

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