Introducing Artificial Intelligence Query With fuzzy query over fuzzy database

Abstract

Information systems have revolutionized the way information can be stored andprocessed. As a result, the information volume has significantly increased leading to aninformation overload. It therefore becomes difficult to analyze the large amounts of availabledata and to generate appropriate management decisions. In practice, information systemsmostly use relational databases in order to store these data collections. Another issue, usingthe relational model, is the restriction of having sharp, precise data and therefore adichotomous querying process which is not well suited for decision making. This paperpresents an artificial intelligent query system using fuzzy logic. The system is based onconstructing a sample fuzzy database and is organized with fuzzy queries, employing vagueor fuzzy terms in the database. The fuzzily defined data has been represented using s, z, and πshaped membership functions. This paper also makes a comparison between traditionaldatabase and fuzzy database by computing the time cost of classical query over classicaldatabase, fuzzy query over classical database and fuzzy query over fuzzy database.Experimental results demonstrate that the proposed intelligent fuzzy query is faster than theconventional query and it provides the user the flexibility to query the database using naturallanguage.