Semantic of data dependencies to improve the data quality

Houda Zaidi*, Yann Pollet, Faouzi Boufarès, Naoufel Kraiem

*المؤلف المقابل لهذا العمل

نتاج البحث: Conference contribution

1 اقتباس (Scopus)

ملخص

Data quality in databases is a critical challenge because the cost of anomalies may be very high, especially for large databases. Therefore, the correction of these anomalies represents an issue that has become more and more important both in enterprises and in academia. In this work, we address the problems of intra-column and inter-columns anomalies in big data. We propose a new approach for data cleaning that takes into account the semantic dependencies between the columns of a data source. The novelty of our proposal is the reduction of the size of the search space in the process of functional dependency discovery based on data semantics. In this paper, we present the first steps of our work. They allow recognizing the semantics of data and correct intra-column anomalies.

اللغة الأصليةEnglish
عنوان منشور المضيفModel and Data Engineering - 5th International Conference, MEDI 2015, Proceedings
المحررونYannis Manolopoulos, Ladjel Bellatreche
ناشرSpringer Verlag
الصفحات53-61
عدد الصفحات9
رقم المعيار الدولي للكتب (المطبوع)9783319237800
المعرِّفات الرقمية للأشياء
حالة النشرPublished - 2015
منشور خارجيًانعم
الحدث5th International Conference on Model and Data Engineering, MEDI 2015 - Rhodes, Greece
المدة: سبتمبر ٢٦ ٢٠١٥سبتمبر ٢٨ ٢٠١٥

سلسلة المنشورات

الاسمLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
مستوى الصوت9344
رقم المعيار الدولي للدوريات (المطبوع)0302-9743
رقم المعيار الدولي للدوريات (الإلكتروني)1611-3349

Other

Other5th International Conference on Model and Data Engineering, MEDI 2015
الدولة/الإقليمGreece
المدينةRhodes
المدة٩/٢٦/١٥٩/٢٨/١٥

ASJC Scopus subject areas

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