کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
402175 676872 2016 20 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Mapping RDF knowledge bases using exchange samples
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Mapping RDF knowledge bases using exchange samples
چکیده انگلیسی

Nowadays, the Web of Data is in its earliest stages; it is currently organised into a variety of linked knowledge bases that have been developed independently by different organisations. RDF is one of the most popular languages to represent data in this context, which motivates the need to perform complex integration tasks amongst RDF knowledge bases. These tasks are performed using schema mappings, which are declarative specifications of the relationships amongst a source and a target knowledge base. Generating schema mappings automatically is appealing because this relieves users from the burden of handcrafting them. In the literature, the vast majority of proposals are based on the data models of the knowledge bases to be integrated, that is, on classes, properties, and constraints. In the Web of Data, there exist many data models that comprise very few constraints or no constraints at all, which has motivated some researchers to work on an alternate paradigm that does not rely on constraints. Unfortunately, the current proposals that fit this paradigm are not completely automatic. In this article, we present our proposal to automatically generate schema mappings amongst RDF knowledge bases. Its salient features are that it uses a single input exchange sample and a set of input correspondences, but does not require any constraints to be available or any user intervention; it has been validated and evaluated using many experiments that prove that it is effective and efficient in practice; the schema mappings that it produces are GLAV. Other researchers can reproduce our experiments since all of our implementations and repositories are publicly available.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Knowledge-Based Systems - Volume 93, 1 February 2016, Pages 47–66
نویسندگان
, , , ,