Hon, Wing-KaiLam, Tak-WahShah, RahulSiu-Lung, TamVitter, Jeffrey Scott2011-03-212011-03-212008W.-K. Hon, T.-W. Lam, R. Shah, S.-L. Tam, and J. S. Vitter. “Compressed Index for Dictionary Matching,” in preparation. An extended abstract appears in Proceedings of the 2008 IEEE Data Compression Conference (DCC ’08), Snowbird, UT, March 2008, 23-32. http://dx.doi.org/10.1109/DCC.2008.62https://hdl.handle.net/1808/7232(c) 2008 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.The past few years have witnessed several exciting results on compressed represen- tation of a string T that supports e±cient pattern matching, and the space complexity has been reduced to jTjHk(T)+o(jTj log ¾) bits [8, 10], where Hk(T) denotes the kth- order empirical entropy of T, and ¾ is the size of the alphabet. In this paper we study compressed representation for another classical problem of string indexing, which is called dictionary matching in the literature. Precisely, a collection D of strings (called patterns) of total length n is to be indexed so that given a text T, the occurrences of the patterns in T can be found e±ciently. In this paper we show how to exploit a sampling technique to compress the existing O(n)-word index to an (nHk(D) + o(n log ¾))-bit index with only a small sacri¯ce in search time.en-USArticle10.1109/DCC.2008.62openAccess