Pattern Matching is coming of age. The last six years have seen great progress in the area of Pattern Matching Algorithms. In particular, researchers have looked into generalized versions of the problem. The field has evolved from being an important theoretical foundational area to being well-poised on the verge of practical usability in many diverse applications, from multi-media to computational molecular biology. The project is seeking a pro-active role in bringing these new results into the relevant applicant domains, as well as feedback and direction about the important missing parts in the theory of pattern matching. This involves joining some large applied projects as an algorithmic group. The research problems described here are motivated and inspired by the needs of these projects. These problems require achieving new insights into the nature of pattern matching, as well as results of the following nature: Efficient algorithms for association generation in dynamic data bases. Efficient generation of generalized associations (e.g. with negations). Efficient algorithms for approximate matching in hyper-text. Efficient algorithms for approximate dictionary matching. New multidimensional adaptive compression schemes that allow efficient compressed searches and space and time efficient local decompression. Generalization of Pattern Matching.
