تقرير
Schema Matching using Machine Learning
العنوان: | Schema Matching using Machine Learning |
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المؤلفون: | Sahay, Tanvi, Mehta, Ankita, Jadon, Shruti |
سنة النشر: | 2019 |
المجموعة: | Computer Science |
مصطلحات موضوعية: | Computer Science - Databases, Computer Science - Artificial Intelligence, Computer Science - Information Retrieval |
الوصف: | Schema Matching is a method of finding attributes that are either similar to each other linguistically or represent the same information. In this project, we take a hybrid approach at solving this problem by making use of both the provided data and the schema name to perform one to one schema matching and introduce the creation of a global dictionary to achieve one to many schema matching. We experiment with two methods of one to one matching and compare both based on their F-scores, precision, and recall. We also compare our method with the ones previously suggested and highlight differences between them. Comment: 7 pages, 2 figures, 2 tables |
نوع الوثيقة: | Working Paper |
DOI: | 10.1109/SPIN48934.2020.9071272 |
URL الوصول: | http://arxiv.org/abs/1911.11543 |
رقم الأكسشن: | edsarx.1911.11543 |
قاعدة البيانات: | arXiv |
DOI: | 10.1109/SPIN48934.2020.9071272 |
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