by Jungh K
For this week’s blog assignment, I read an article, titled “A New Upgrade to SQLf: Towards a Standard in Fuzzy Databases”. The article discusses three new features of SQLf and proposes them to be incorporated into SQL:2003 standards. One such feature is fuzzy table storage which extends from CREATE TABLE statement to create a fuzzy table. Second feature is fuzzy multiset data type which supports both algebraic operations and new aggregate functions. Third and the last feature is fuzzy merge statement which merges two or more tables that meet the certain “satisfaction of degree”. Using fuzzy sets in a traditional DBMS is a much more complex process since Boolean conditions return less number of rows that meet the given conditions and therefore it requires more processes to refine the data. In conclusion, extensions of the three fuzzy features would change the underlying data model to a Fuzzy Relational Model.
In this week’s class meeting, the professor demonstrated how SQL statements, such as INSERT, UPDATE, SELECT, CREATE, and so on, work to manipulate raw data. The article I read for this week extends into how raw data are transformed into information. Using fuzzy logics would enable a user to incorporate “satisfaction of degree” when he or she queries for specific data to refine the data. For instance, the article uses examples where quantifiers, such as “most of”, “about a half”, and “around”, are useful in real life scenarios. Also, in the first week of the class, we learned about difference between data and information. SQL, in a sense, is storage for data and therefore data have to be converted into information to be used as a decision supporting tool.
Gonzalez, C.; Goncalves, M.; Tineo, L.; , “A New Upgrade to SQLf: Towards a Standard in Fuzzy Databases,” Database and Expert Systems Application, 2009. DEXA ’09. 20th International Workshop on , vol., no., pp.442-446, Aug. 31 2009-Sept. 4 2009