On Hardness of Several String Indexing Problems

Abstract

Let \({\cal D} =\{d_1,d_2,...,d_D\}\) be a collection of D string documents of n characters in total. The two-pattern matching problems ask to index \({\cal D}\) for answering the following queries efficiently. report/count the unique documents containing P 1 and P 2. report/count the unique documents containing P 1 , but not P 2. Here P 1 and P 2 represent input patterns of length p 1 and p 2 respectively. Linear space data structures with \(O(p_1+p_2+\sqrt{nk}\log^{O(1)} n)\) query cost are already known for the reporting version, where k represents the output size. For the counting version (i.e., report the value k), a simple linear-space index with \(O(p_1+p_2+ \sqrt{n})\) query cost can be constructed in O(n 3/2) time. However, it is still not known if these are the best possible bounds for these problems. In this paper, we show a strong connection between these string indexing problems and the boolean matrix multiplication problem. Based on this, we argue that these results cannot be improved significantly using purely combinatorial techniques. We also provide an improved upper bound for a related problem known as two-dimensional substring indexing.KeywordsQuery TimeBoolean MatrixOutput SizeWord StructureBoolean MatriceThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.