The palindromic tree (a.k.a. eertree) for a string S of length n is a tree-like data structure that represents the set of all distinct palindromic substrings of S, using O(n) space [Rubinchik and Shur, 2018]. It is known that, when S is over an alphabet of size σ and is given in an online manner, then the palindromic tree of S can be constructed in O(nlog⁡σ) time with O(n) space. In this paper, we consider the sliding window version of the problem: For a sliding window of length at most d, we present two versions of an algorithm which maintains the palindromic tree of size O(d) for every sliding window S[i..j] over S, where 1≤j−i+1≤d. The first version works in O(nlog⁡σ′) time with O(d) space where σ′≤d is the maximum number of distinct characters in the windows, and the second one works in O(n+dσ) time with (d+2)σ+O(d) space. We also show how our algorithms can be applied to efficient computation of minimal unique palindromic substrings (MUPS) and minimal absent palindromic words (MAPW) for a sliding window.

Given a dynamic set K of k strings of total length n whose characters are drawn from an alphabet of size σ, a keyword dictionary is a data structure built on K that provides locate, prefix search, and update operations on K. Under the assumption that α = w / lg σ characters fit into a single machine word w, we propose a keyword dictionary that represents K in n lg σ + Θ(k lg n) bits of space, supporting all operations in Θ(m / α + lg α) expected time on an input string of length m in the word RAM model. This data structure is underlined with an exhaustive practical evaluation, highlighting the practical usefulness of the proposed data structure, especially for prefix searches - one of the most elementary keyword dictionary operations.

We analyze the grammar generation algorithm of the RePair compression algorithm and show the relation between a grammar generated by RePair and maximal repeats. We reveal that RePair replaces step by step the most frequent pairs within the corresponding most frequent maximal repeats. Then, we design a novel variant of RePair, called MR-RePair, which substitutes the most frequent maximal repeats at once instead of substituting the most frequent pairs consecutively. We implemented MR-RePair and compared the size of the grammar generated by MR-RePair to that by RePair on several text corpora. Our experiments show that MR-RePair generates more compact grammars than RePair does, especially for highly repetitive texts.

In this paper, we present efficient algorithms for interconversion between Lempel-Ziv 78 (LZ78) encoding and run length encoding (RLE). We show how, given an RLE of size n for a string S, we can compute the corresponding LZ78 encoding of size m for S in O((n + m) log σ) time, where σ is the number of distinct characters appearing in S. We also show how, given an LZ78 encoding of size m for a string S, we can compute the corresponding RLE of size n in O(n + m) time. Both algorithms use O(m) extra working space.

The convolution between a text string S of length N and a pattern string P of length m can be computed in O(N log m) time by FFT. It is known that various types of approximate string matching problems are reducible to convolution. In this paper, we assume that the input text string is given in a compressed form, as a straight-line program (SLP), which is a context free grammar in the Chomsky normal form that derives a single string. Given an SLP S of size n describing a text S of length N, and an uncompressed pattern P of length m, we present a simple O(nm log m)-time algorithm to compute the convolution between S and P. We then show that this can be improved to O(min{nm, N - α} log m) time, where α ≥ 0 is a value that represents the amount of redundancy that the SLP captures with respect to the length-m substrings. The key of the improvement is our new algorithm that computes the convolution between a trie of size r and a pattern string P of length m in O(r log m) time.

We consider grammar based text compression with longest-first substitution, where non-overlapping occurrences of a longest repeating substring of the input text are replaced by a new non-terminal symbol. We present a new text compression algorithm by simplifying the algorithm presented in S. Inenaga et al., (2003). We give a new formulation of the correctness proof introducing the sparse lazy suffix tree data structure. We also present another type of longest-first substitution strategy that allows better compression. We show results of preliminary experiments comparing grammar sizes of the two versions of the longest-first strategy and the most frequent strategy

The Compact Directed Acyclic Word Graph (CDAWG) is a space-eflcient data structure that supports indices of a string. The Symmetric Directed Acyclic Word Graph (SCDAWG) for a string w is a dual structure that supports indices of both w and the reverse of w simultaneously. Blumer et al. gave the first algorithm to construct an SCDAWG from a given string, that works in an of-line manner. In this papec we show an on-line algorithm that constructs an SCDAWGfiom a given string directly.