Gradual inference rules in approximate reasoning
Information Sciences: an International Journal
What are fuzzy rules and how to use them
Fuzzy Sets and Systems - Special issue dedicated to the memory of Professor Arnold Kaufmann
Extended Functional Dependencies as a Basis for Linguistic Summaries
PKDD '98 Proceedings of the Second European Symposium on Principles of Data Mining and Knowledge Discovery
Checking the coherence and redundancy of fuzzy knowledge bases
IEEE Transactions on Fuzzy Systems
Generating Fuzzy Summaries from Fuzzy Multidimensional Databases
IDA '01 Proceedings of the 4th International Conference on Advances in Intelligent Data Analysis
Mining Frequent Gradual Itemsets from Large Databases
IDA '09 Proceedings of the 8th International Symposium on Intelligent Data Analysis: Advances in Intelligent Data Analysis VIII
Efficient discovery of generalized sentinel rules
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part II
Hi-index | 0.00 |
With the increasing size of databases, the extraction of data summaries becomes more and more useful. The use of fazzy sets seems interesting in order to extract linguistic summaries, i.e., statements from the natural language, containing gradual properties, which are meaningful for human operators. This paper focuses on the extraction from databases of linguistic summaries, using so-called fuzzy gradual rules, which encode statements of the form "the younger the employees, the smaller their bonus". The summaries considered here are more on the relations between labels of the attributes than on the data themselves. The first idea is to extract all the rules which are not in contradiction with tuples of a given relation. Then, the interest of these rules is questioned. For instance, some of them can reveal potential incoherence, while other are not really informative. It is then shown that in some cases, interesting information can be extracted from these rules. Last, some properties the final set of rules should verify are outlined.