Keywords Sequenced Data, Database Queries, Expressiveness, Optimization, Data Mining. In many database applications, the order among data items plays an important role. To query such sequenced data, current systems depend on recursion or iteration constructs found in programming languages. Although powerful enough to express all computable queries, these constructs are unnatural in expressing many intuitive queries and difficult to optimize. This research focuses on overcoming such drawbacks by studying and developing declarative query languages on sequenced data, as well as data mining techniques.
Experimental work is to be performed to test proposed query formation and optimization.
The project, in its fourth year now, focuses on order-oriented queries for decision support systems and data mining tasks involving sequenced data. For decision support systems, an extension of SQL is introduced to deal with order related queries in business data in a uniform way. Optimization and related problems will be further studied. On the data mining front, the objective is to study algorithms and methods to discover sequential patterns in an efficient way by exploiting special properties of sequenced data. Experiments are planned to study the effectiveness of the developed methods.