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Masayuki Takeda

Publications and source records attributed to Masayuki Takeda.

At least 19 recordsLinked to original sources

Online Computation of Palindromes and Suffix Trees on Tries

We consider the problems of computing maximal palindromes and distinct palindromes in a trie. A trie is a natural generalization of a string, which can be seen as a single-path tree. There is a linear-time offline algorithm to compute maximal palindromes and distinct palindromes in a given (static) trie whose edge-labels are drawn from a linearly-sortable alphabet [Mieno et al., ISAAC 2022]. In this paper, we tackle problems of palindrome enumeration on dynamic tries which support leaf additions and leaf deletions. We propose the first sub-quadratic algorithms to enumerate palindromes in a dynamic trie. For maximal palindromes, we propose an algorithm that runs in $O(N \min(\log h, σ))$ time and uses $O(N)$ space, where $N$ is the maximum number of edges in the trie, $σ$ is the size of the alphabet, and $h$ is the height of the trie. For distinct palindromes, we develop several online algorithms based on different algorithmic frameworks, including approaches using the EERTREE (a.k.a. palindromic tree) and the suffix tree of a trie. These algorithms support leaf insertions and deletions in the trie and achieve different time and space trade-offs. Furthermore, as a by-product, we present online algorithms to construct the suffix tree and the EERTREE of the input trie, which is of independent interest.

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Computing maximal palindromes in non-standard matching models

Palindromes are popular and important objects in textual data processing, bioinformatics, and combinatorics on words. Let $S = XaY$ be a string where $X$ and $Y$ are of the same length, and $a$ is either a single character or the empty string. Then, there exist two alternative definitions for palindromes: $S$ is said to be a palindrome if $S$ is equal to its reversal $S^R$ (Reversal-based definition); or if its right-arm $Y$ is equal to the reversal of its left-arm $X^R$ (Symmetry-based definition). It is clear that if the ``equality'' ($\approx$) used in both definitions is exact character matching ($=$), then the two definitions are the same. However, if we apply other string-equality criteria $\approx$, including the complementary-matching model for biological sequences, the Cartesian-tree model [Park et al., TCS 2020], the parameterized model [Baker, JCSS 1996], the order-preserving model [Kim et al., TCS 2014], and the palindromic-structure model [I et al., TCS 2013], then are the reversal-based palindromes and the symmetry-based palindromes the same? To the best of our knowledge, no previous work has considered or answered this natural question. In this paper, we first provide answers to this question, and then present efficient algorithms for computing all maximal palindromes under the non-standard matching models in a given string. After confirming that Gusfield's offline suffix-tree-based algorithm for computing maximal symmetry-based palindromes can be readily extended to the aforementioned matching models, we show how to extend Manacher's online algorithm for computing maximal reversal-based palindromes in linear time for all the aforementioned matching models.

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Linear-time Computation of DAWGs, Symmetric Indexing Structures, and MAWs for Integer Alphabets

The directed acyclic word graph (DAWG) of a string $y$ of length $n$ is the smallest (partial) DFA which recognizes all suffixes of $y$ with only $O(n)$ nodes and edges. In this paper, we show how to construct the DAWG for the input string $y$ from the suffix tree for $y$, in $O(n)$ time for integer alphabets of polynomial size in $n$. In so doing, we first describe a folklore algorithm which, given the suffix tree for $y$, constructs the DAWG for the reversed string of $y$ in $O(n)$ time. Then, we present our algorithm that builds the DAWG for $y$ in $O(n)$ time for integer alphabets, from the suffix tree for $y$. We also show that a straightforward modification to our DAWG construction algorithm leads to the first $O(n)$-time algorithm for constructing the affix tree of a given string $y$ over an integer alphabet. Affix trees are a text indexing structure supporting bidirectional pattern searches. We then discuss how our constructions can lead to linear-time algorithms for building other text indexing structures, such as linear-size suffix tries and symmetric CDAWGs in linear time in the case of integer alphabets. As a further application to our $O(n)$-time DAWG construction algorithm, we show that the set $\mathsf{MAW}(y)$ of all minimal absent words (MAWs) of $y$ can be computed in optimal, input- and output-sensitive $O(n + |\mathsf{MAW}(y)|)$ time and $O(n)$ working space for integer alphabets.

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Parameterized DAWGs: efficient constructions and bidirectional pattern searches

Two strings $x$ and $y$ over $Σ\cup Π$ of equal length are said to \emph{parameterized match} (\emph{p-match}) if there is a renaming bijection $f:Σ\cup Π\rightarrow Σ\cup Π$ that is identity on $Σ$ and transforms $x$ to $y$ (or vice versa). The \emph{p-matching} problem is to look for substrings in a text that p-match a given pattern. In this paper, we propose \emph{parameterized suffix automata} (\emph{p-suffix automata}) and \emph{parameterized directed acyclic word graphs} (\emph{PDAWGs}) which are the p-matching versions of suffix automata and DAWGs. While suffix automata and DAWGs are equivalent for standard strings, we show that p-suffix automata can have $Θ(n^2)$ nodes and edges but PDAWGs have only $O(n)$ nodes and edges, where $n$ is the length of an input string. We also give an $O(n |Π| \log (|Π| + |Σ|))$-time $O(n)$-space algorithm that builds the PDAWG in a left-to-right online manner. As a byproduct, it is shown that the \emph{parameterized suffix tree} for the reversed string can also be built in the same time and space, in a right-to-left online manner. This duality also leads us to two further efficient algorithms for p-matching: Given the parameterized suffix tree for the reversal of the input string $T$, one can build the PDAWG of $T$ in $O(n)$ time in an offline manner; One can perform \emph{bidirectional} p-matching in $O(m \log (|Π|+|Σ|) + \mathit{occ})$ time using $O(n)$ space, where $m$ denotes the pattern length and $\mathit{occ}$ is the number of pattern occurrences in the text $T$.

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Combinatorics of minimal absent words for a sliding window

A string $w$ is called a minimal absent word (MAW) for another string $T$ if $w$ does not occur in $T$ but the proper substrings of $w$ occur in $T$. For example, let $Σ= \{\mathtt{a, b, c}\}$ be the alphabet. Then, the set of MAWs for string $w = \mathtt{abaab}$ is $\{\mathtt{aaa, aaba, bab, bb, c}\}$. In this paper, we study combinatorial properties of MAWs in the sliding window model, namely, how the set of MAWs changes when a sliding window of fixed length $d$ is shifted over the input string $T$ of length $n$, where $1 \leq d < n$. We present \emph{tight} upper and lower bounds on the maximum number of changes in the set of MAWs for a sliding window over $T$, both in the cases of general alphabets and binary alphabets. Our bounds improve on the previously known best bounds [Crochemore et al., 2020].

math.CO

On the approximation ratio of LZ-End to LZ77

A family of Lempel-Ziv factorizations is a well-studied string structure. The LZ-End factorization is a member of the family that achieved faster extraction of any substrings (Kreft & Navarro, TCS 2013). One of the interests for LZ-End factorizations is the possible difference between the size of LZ-End and LZ77 factorizations. They also showed families of strings where the approximation ratio of the number of LZ-End phrases to the number of LZ77 phrases asymptotically approaches 2. However, the alphabet size of these strings is unbounded. In this paper, we analyze the LZ-End factorization of the period-doubling sequence. We also show that the approximation ratio for the period-doubling sequence asymptotically approaches 2 for the binary alphabet.

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Counting Lyndon Subsequences

Counting substrings/subsequences that preserve some property (e.g., palindromes, squares) is an important mathematical interest in stringology. Recently, Glen et al. studied the number of Lyndon factors in a string. A string $w = uv$ is called a Lyndon word if it is the lexicographically smallest among all of its conjugates $vu$. In this paper, we consider a more general problem "counting Lyndon subsequences". We show (1) the maximum total number of Lyndon subsequences in a string, (2) the expected total number of Lyndon subsequences in a string, (3) the expected number of distinct Lyndon subsequences in a string.

math.CO

Grammar Index By Induced Suffix Sorting

Pattern matching is the most central task for text indices. Most recent indices leverage compression techniques to make pattern matching feasible for massive but highly-compressible datasets. Within this kind of indices, we propose a new compressed text index built upon a grammar compression based on induced suffix sorting [Nunes et al., DCC'18]. We show that this grammar exhibits a locality sensitive parsing property, which allows us to specify, given a pattern $P$, certain substrings of $P$, called cores, that are similarly parsed in the text grammar whenever these occurrences are extensible to occurrences of $P$. Supported by the cores, given a pattern of length $m$, we can locate all its $occ$ occurrences in a text $T$ of length $n$ within $O(m \lg |\mathcal{S}| + occ_C \lg|\mathcal{S}| \lg n + occ)$ time, where $\mathcal{S}$ is the set of all characters and non-terminals, $occ$ is the number of occurrences, and $occ_C$ is the number of occurrences of a chosen core $C$ of $P$ in the right hand side of all production rules of the grammar of $T$. Our grammar index requires $O(g)$ words of space and can be built in $O(n)$ time using $O(g)$ working space, where $g$ is the sum of the right hand sides of all production rules. We underline the strength of our grammar index with an exhaustive practical evaluation that gives evidence that our proposed solution excels at locating long patterns in highly-repetitive texts.

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Efficiently computing runs on a trie

A maximal repetition, or run, in a string, is a maximal periodic substring whose smallest period is at most half the length of the substring. In this paper, we consider runs that correspond to a path on a trie, or in other words, on a rooted edge-labeled tree where the endpoints of the path must be a descendant/ancestor of the other. For a trie with $n$ edges, we show that the number of runs is less than $n$. We also show an asymptotic lower bound on the maximum density of runs in tries: $\lim_{n\rightarrow\infty}ρ_\mathcal{T}(n)/n \geq 0.993238$ where $ρ_{\mathcal{T}}(n)$ is the maximum number of runs in a trie with $n$ edges. Furthermore, we also show an $O(n\log \log n)$ time and $O(n)$ space algorithm for finding all runs.

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Compressed Communication Complexity of Hamming Distance

We consider the communication complexity of the Hamming distance of two strings. Bille et al. [SPIRE 2018] considered the communication complexity of the longest common prefix (LCP) problem in the setting where the two parties have their strings in a compressed form, i.e., represented by the Lempel-Ziv 77 factorization (LZ77) with/without self-references. We present a randomized public-coin protocol for a joint computation of the Hamming distance of two strings represented by LZ77 without self-references. While our scheme is heavily based on Bille et al.'s LCP protocol, our complexity analysis is original which uses Crochemore's C-factorization and Rytter's AVL-grammar. As a byproduct, we also show that LZ77 with/without self-references are not monotonic in the sense that their sizes can increase by a factor of 4/3 when a prefix of the string is removed.

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The Parameterized Suffix Tray

Let $Σ$ and $Π$ be disjoint alphabets, respectively called the static alphabet and the parameterized alphabet. Two strings $x$ and $y$ over $Σ\cup Π$ of equal length are said to parameterized match (p-match) if there exists a renaming bijection $f$ on $Σ$ and $Π$ which is identity on $Σ$ and maps the characters of $x$ to those of $y$ so that the two strings become identical. The indexing version of the problem of finding p-matching occurrences of a given pattern in the text is a well-studied topic in string matching. In this paper, we present a state-of-the-art indexing structure for p-matching called the parameterized suffix tray of an input text $T$, denoted by $\mathsf{PSTray}(T)$. We show that $\mathsf{PSTray}(T)$ occupies $O(n)$ space and supports pattern matching queries in $O(m + \log (σ+π) + \mathit{occ})$ time, where $n$ is the length of $T$, $m$ is the length of a query pattern $P$, $π$ is the number of distinct symbols of $|Π|$ in $T$, $σ$ is the number of distinct symbols of $|Σ|$ in $T$ and $\mathit{occ}$ is the number of p-matching occurrences of $P$ in $T$. We also present how to build $\mathsf{PSTray}(T)$ in $O(n)$ time from the parameterized suffix tree of $T$.

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Computing longest palindromic substring after single-character or block-wise edits

Palindromes are important objects in strings which have been extensively studied from combinatorial, algorithmic, and bioinformatics points of views. It is known that the length of the longest palindromic substrings (LPSs) of a given string T of length n can be computed in O(n) time by Manacher's algorithm [J. ACM '75]. In this paper, we consider the problem of finding the LPS after the string is edited. We present an algorithm that uses O(n) time and space for preprocessing, and answers the length of the LPSs in O(\log (\min \{σ, \log n\})) time after a single character substitution, insertion, or deletion, where σdenotes the number of distinct characters appearing in T. We also propose an algorithm that uses O(n) time and space for preprocessing, and answers the length of the LPSs in O(\ell + \log \log n) time, after an existing substring in T is replaced by a string of arbitrary length \ell.

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Palindromic Trees for a Sliding Window and Its Applications

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 $O(n\logσ)$ 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 $1 \leq j-i+1 \leq d$. The first version works in $O(n\logσ')$ time with $O(d)$ space where $σ' \leq d$ 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.

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c-trie++: A Dynamic Trie Tailored for Fast Prefix Searches

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 $O(m / α+ \lg α)$ 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.

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Space-Efficient Algorithms for Computing Minimal/Shortest Unique Substrings

Given a string $T$ of length $n$, a substring $u = T[i..j]$ of $T$ is called a shortest unique substring (SUS) for an interval $[s,t]$ if (a) $u$ occurs exactly once in $T$, (b) $u$ contains the interval $[s,t]$ (i.e. $i \leq s \leq t \leq j$), and (c) every substring $v$ of $T$ with $|v| < |u|$ containing $[s,t]$ occurs at least twice in $T$. Given a query interval $[s, t] \subset [1, n]$, the interval SUS problem is to output all the SUSs for the interval $[s,t]$. In this article, we propose a $4n + o(n)$ bits data structure answering an interval SUS query in output-sensitive $O(\mathit{occ})$ time, where $\mathit{occ}$ is the number of returned SUSs. Additionally, we focus on the point SUS problem, which is the interval SUS problem for $s = t$. Here, we propose a $\lceil (\log_2{3} + 1)n \rceil + o(n)$ bits data structure answering a point SUS query in the same output-sensitive time. We also propose space-efficient algorithms for computing the minimal unique substrings of $T$.

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On repetitiveness measures of Thue-Morse words

We show that the size $γ(t_n)$ of the smallest string attractor of the $n$th Thue-Morse word $t_n$ is 4 for any $n\geq 4$, disproving the conjecture by Mantaci et al. [ICTCS 2019] that it is $n$. We also show that $δ(t_n) = \frac{10}{3+2^{4-n}}$ for $n \geq 3$, where $δ(w)$ is the maximum over all $k = 1,\ldots,|w|$, the number of distinct substrings of length $k$ in $w$ divided by $k$, which is a measure of repetitiveness recently studied by Kociumaka et al. [LATIN 2020]. Furthermore, we show that the number $z(t_n)$ of factors in the self-referencing Lempel-Ziv factorization of $t_n$ is exactly $2n$.

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Towards Efficient Interactive Computation of Dynamic Time Warping Distance

The dynamic time warping (DTW) is a widely-used method that allows us to efficiently compare two time series that can vary in speed. Given two strings $A$ and $B$ of respective lengths $m$ and $n$, there is a fundamental dynamic programming algorithm that computes the DTW distance for $A$ and $B$ together with an optimal alignment in $Θ(mn)$ time and space. In this paper, we tackle the problem of interactive computation of the DTW distance for dynamic strings, denoted $\mathrm{D^2TW}$, where character-wise edit operation (insertion, deletion, substitution) can be performed at an arbitrary position of the strings. Let $M$ and $N$ be the sizes of the run-length encoding (RLE) of $A$ and $B$, respectively. We present an algorithm for $\mathrm{D^2TW}$ that occupies $Θ(mN+nM)$ space and uses $O(m+n+\#_{\mathrm{chg}}) \subseteq O(mN + nM)$ time to update a compact differential representation $\mathit{DS}$ of the DP table per edit operation, where $\#_{\mathrm{chg}}$ denotes the number of cells in $\mathit{DS}$ whose values change after the edit operation. Our method is at least as efficient as the algorithm recently proposed by Froese et al. running in $Θ(mN + nM)$ time, and is faster when $\#_{\mathrm{chg}}$ is smaller than $O(mN + nM)$ which, as our preliminary experiments suggest, is likely to be the case in the majority of instances.

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Grammar-compressed Self-index with Lyndon Words

We introduce a new class of straight-line programs (SLPs), named the Lyndon SLP, inspired by the Lyndon trees (Barcelo, 1990). Based on this SLP, we propose a self-index data structure of $O(g)$ words of space that can be built from a string $T$ in $O(n \lg n)$ expected time, retrieving the starting positions of all occurrences of a pattern $P$ of length $m$ in $O(m + \lg m \lg n + occ \lg g)$ time, where $n$ is the length of $T$, $g$ is the size of the Lyndon SLP for $T$, and $occ$ is the number of occurrences of $P$ in $T$.

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