This problem would be especially evident in the case of databases that do not get updated frequently or that have been abandoned completely.
As can be observed, the result of the experiments in the case of heterogeneous database outperforms that of the experiments in the case of only-plastic-surgery database.
In the case of MUBA database, the improvement is very relevant: identification rate reaches an 95%% and false alarm rate decreases to 4.84 % when K increases.
In the case of a database source, the compilation process determines the most efficient series of table joins to retrieve the requested data and creates an SQL statement.
In the case of relational databases, there are standard APIs (e.g., JDBC), which do not exist yet for document databases, such as MongoDB or Apache CouchDB.
In the case of relational databases, accesses are normally done over simple data types (e.g., strings, integers, dates); however, when NoSQL databases are used, storing and accessing full documents is a quite typical case.
In the case of Oracle databases, most fees are high and per processor, which means things get expensive quickly, eating up IT budgets.
Each of these data schemas allows for filtering by a query language (QL): SQL in the case of relational databases, XQuery in the case of XML data and SPARQL in the case of RDF data.
In the case of dense databases, tries are used as this type of base generates few branches and intensifies mining efficiency.
In the case of diabetes, databases on body composition, strength, and function in large clinical series of patients are greatly needed and might be feasible ancillary studies to the many existing multicenter observational and intervention programs.
In the case of simulated databases, no QC filters were applied because the MAF has been defined in such a way to be greater than 10% and less than 40%.
