Sentence examples for database normalization from inspiring English sources
In order to reduce the redundancy of the database and improve the data quality and integrity, we adopted relational database normalization to parse the raw data table into a second normal form schema. Through the normalization process, potential errors such as duplicate entries, misplaced taxa, etc., could be eliminated efficiently.
It also highlights database design models and database normalization, which refers to the optimization process of the database.
We present two approaches in database designs and discuss the performance of Gamma on the extensive computation involved in the relational database normalization process.
Conventionally, features such as harmonics-to-noise ratio [27] and preprocessing methods like database normalization involving speaker, corpus, language, or gender are used to cope with the need of defining a reference criteria [14] in emotion detection.
Database normalization was introduced by Codd in 1970 (33).
To enhance database normalization, we make the 'Entrez ID' field in 'Genes_go' as a foreign key and have it relate to the 'Genes' table.
After database size normalization, the average normalized false positives versus effective variable curves of a given method will become close.
In this paper, we exploit the expressiveness of Gamma to elegantly and succinctly specify the normalization aspects in relational databases and use its computational power to achieve greater performance in verifying and realizing relational database normal forms.
A summary of the number of pathways, genes and gene pairs from different databases after normalization is given in Table 2. To tackle inconsistent molecular relationship representations, we also normalized the relationships of different databases into the IntPath unified relationship types as shown in Table 1.
The extracted intensity data from the mAdb database were normalized by Lowess normalization method and analyzed by modified t-statistic Significance Analysis of Microarrays (SAM) [97].
Challenge Evaluation tasks over the years have included ranking of relevant documents (document triage), extraction of genes and proteins (gene mention) and their linkage to database identifiers (gene normalization), as well as extraction of functional annotation in standard ontologies (e.g. Gene Ontology (10)) and extraction of entity relations (e.g. protein protein interaction).
