Stefan Böttcher, Rita Hartel, Sven Peeters
Like [1], we present an algorithm to compute the simulation of a query pattern in a graph of labeled nodes and unlabeled edges. However, our algorithm works on a compressed graph grammar, instead of on the original graph. The speed-up of our algorithm compared to the algorithm in [1] grows with the size of the graph and with the compression strength.
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Cadences are structurally maximal arithmetic progressions of indices corresponding to equal characters in an underlying string. This paper provides a polynomial time detection algorithm for 3-cadences in grammar-compressed binary strings. This algorithm also translates to a linear time detection algorithm for 3-cadences in uncompressed binary strings. Furthermore, this paper proves that several variants of the cadence detection problem are NP-complete for grammar-compressed strings. As a consequence, the equidistant subsequence matching problem with patterns of length three is NP-complete for …
A grammar-compressed ranked tree is represented with a linear space overhead so that a single traversal step, i.e., the move to the parent or the i-th child, can be carried out in constant time. Moreover, we extend our data structure such that equality of subtrees can be checked in constant time.
Let a text $T[1..n]$ be the only string generated by a context-free grammar with $g$ (terminal and nonterminal) symbols, and of size $G$ (measured as the sum of the lengths of the right-hand sides of the rules). Such a grammar, called a grammar-compressed representation of $T$, can be encoded using essentially $G\lg g$ bits. We introduce the first grammar-compressed index that uses $O(G\lg n)$ bits and can find the $occ$ occurrences of patterns $P[1..m]$ in time $O((m^2+occ)\lg G)$. We implement the index and demonstrate its practicality in comparison with the state of the art, on highly repet…
Revisiting the Folklore Algorithm for Random Access to Grammar-Compressed Strings
针对语法压缩字符串随机访问实用研究不足的问题，本文修改了乔姆斯基范式下的民间传说随机访问算法使其适配通用语法，验证了其实际运行速度快、内存效率高的优势。
We introduce the first grammar-compressed representation of a sequence that supports searches in time that depends only logarithmically on the size of the grammar. Given a text $T[1..u]$ that is represented by a (context-free) grammar of $n$ (terminal and nonterminal) symbols and size $N$ (measured as the sum of the lengths of the right hands of the rules), a basic grammar-based representation of $T$ takes $N\lg n$ bits of space. Our representation requires $2N\lg n + N\lg u + ε\, n\lg n + o(N\lg n)$ bits of space, for any $0<ε\le 1$. It can find the positions of the $occ$ occurrences of a pat…
The random access problem for compressed strings is to build a data structure that efficiently supports accessing the character in position $i$ of a string given in compressed form. Given a grammar of size $n$ compressing a string of size $N$, we present a data structure using $O(nΔ\log_Δ\frac N n \log N)$ bits of space that supports accessing position $i$ in $O(\log_ΔN)$ time for $Δ\leq \log^{O(1)} N$. The query time is optimal for polynomially compressible strings, i.e., when $n=O(N^{1-ε})$.
We present an algorithm for computing the Lyndon factorization of a string that is given in grammar compressed form, namely, a Straight Line Program (SLP). The algorithm runs in $O(n^4 + mn^3h)$ time and $O(n^2)$ space, where $m$ is the size of the Lyndon factorization, $n$ is the size of the SLP, and $h$ is the height of the derivation tree of the SLP. Since the length of the decompressed string can be exponentially large w.r.t. $n, m$ and $h$, our result is the first polynomial time solution when the string is given as SLP.
Sequence representations supporting not only direct access to their symbols, but also rank/select operations, are a fundamental building block in many compressed data structures. Several recent applications need to represent highly repetitive sequences, and classical statistical compression proves ineffective. We introduce, instead, grammar-based representations for repetitive sequences, which use up to 6% of the space needed by statistically compressed representations, and support direct access and rank/select operations within tens of microseconds. We demonstrate the impact of our structures…
We present a pointer-based data structure for constant time traversal of the edges of an edge-labeled (alphabet $Σ$) directed hypergraph (a graph where edges can be incident to more than two vertices, and the incident vertices are ordered) given as hyperedge-replacement grammar $G$. It is assumed that the grammar has a fixed rank $κ$ (maximal number of vertices connected to a nonterminal hyperedge) and that each vertex of the represented graph is incident to at most one $σ$-edge per direction ($σ\in Σ$). Precomputing the data structure needs $O(|G||Σ|κr h)$ space and $O(|G||Σ|κrh^2)$ time, whe…
The CDAWG Index and Pattern Matching on Grammar-Compressed Strings
本研究提出将CDAWG用作语法压缩字符串的索引，实现了高效模式匹配，实验验证其运行时性能达当前最优，且空间复杂度符合已知最优渐近界。
Straight-line (linear) context-free tree (SLT) grammars have been used to compactly represent ordered trees. It is well known that equivalence of SLT grammars is decidable in polynomial time. Here we extend this result and show that isomorphism of unordered trees given as SLT grammars is decidable in polynomial time. The proof constructs a compressed version of the canonical form of the tree represented by the input SLT grammar. The result is generalized to unrooted trees by "re-rooting" the compressed trees in polynomial time. We further show that bisimulation equivalence of unrooted unordere…
Grammar based compression, where one replaces a long string by a small context-free grammar that generates the string, is a simple and powerful paradigm that captures many popular compression schemes. In this paper, we present a novel grammar representation that allows efficient random access to any character or substring without decompressing the string. Let $S$ be a string of length $N$ compressed into a context-free grammar $\mathcal{S}$ of size $n$. We present two representations of $\mathcal{S}$ achieving $O(\log N)$ random access time, and either $O(n\cdot α_k(n))$ construction time and …
With massive high-dimensional data now commonplace in research and industry, there is a strong and growing demand for more scalable computational techniques for data analysis and knowledge discovery. Key to turning these data into knowledge is the ability to learn statistical models with high interpretability. Current methods for learning statistical models either produce models that are not interpretable or have prohibitive computational costs when applied to massive data. In this paper we address this need by presenting a scalable algorithm for partial least squares regression (PLS), which w…
We present an algorithm for building the extended BWT (eBWT) of a string collection from its grammar-compressed representation. Our technique exploits the string repetitions captured by the grammar to boost the computation of the eBWT. Thus, the more repetitive the collection is, the lower are the resources we use per input symbol. We rely on a new grammar recently proposed at DCC'21 whose nonterminals serve as building blocks for inducing the eBWT. A relevant application for this idea is the construction of self-indexes for analyzing sequencing reads -- massive and repetitive string collectio…
We present a compressed data structure to store free trajectories of moving objects (ships over the sea, for example) allowing spatio-temporal queries. Our method, GraCT, uses a $k^2$-tree to store the absolute positions of all objects at regular time intervals (snapshots), whereas the positions between snapshots are represented as logs of relative movements compressed with Re-Pair. Our experimental evaluation shows important savings in space and time with respect to a fair baseline.
We investigate two closely related LZ78-based compression schemes: LZMW (an old scheme by Miller and Wegman) and LZD (a recent variant by Goto et al.). Both LZD and LZMW naturally produce a grammar for a string of length $n$; we show that the size of this grammar can be larger than the size of the smallest grammar by a factor $Ω(n^{\frac{1}3})$ but is always within a factor $O((\frac{n}{\log n})^{\frac{2}{3}})$. In addition, we show that the standard algorithms using $Θ(z)$ working space to construct the LZD and LZMW parsings, where $z$ is the size of the parsing, work in $Ω(n^{\frac{5}4})$ ti…
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 $T$.
The most fundamental problem considered in algorithms for text processing is pattern matching: given a pattern $p$ of length $m$ and a text $t$ of length $n$, does $p$ occur in $t$? Multiple versions of this basic question have been considered, and by now we know algorithms that are fast both in practice and in theory. However, the rapid increase in the amount of generated and stored data brings the need of designing algorithms that operate directly on compressed representations of data. In the compressed pattern matching problem we are given a compressed representation of the text, with $n$ b…
The compressed indexing problem is to preprocess a string $S$ of length $n$ into a compressed representation that supports pattern matching queries. That is, given a string $P$ of length $m$ report all occurrences of $P$ in $S$. We present a data structure that supports pattern matching queries in $O(m + occ (\lg\lg n + \lg^εz))$ time using $O(z \lg(n / z))$ space where $z$ is the size of the LZ77 parse of $S$ and $ε> 0$ is an arbitrarily small constant, when the alphabet is small or $z = O(n^{1 - δ})$ for any constant $δ> 0$. We also present two data structures for the general case; one where…
We present an efficient algorithm for calculating $q$-gram frequencies on strings represented in compressed form, namely, as a straight line program (SLP). Given an SLP $\mathcal{T}$ of size $n$ that represents string $T$, the algorithm computes the occurrence frequencies of all $q$-grams in $T$, by reducing the problem to the weighted $q$-gram frequencies problem on a trie-like structure of size $m = |T|-\mathit{dup}(q,\mathcal{T})$, where $\mathit{dup}(q,\mathcal{T})$ is a quantity that represents the amount of redundancy that the SLP captures with respect to $q$-grams. The reduced problem c…
We introduce a compressed data structure for the storage of free trajectories of moving objects (such as ships and planes) that efficiently supports various spatio-temporal queries. Our structure, dubbed GraCT, stores the absolute positions of all the objects at regular time intervals (snapshots) using a $k^2$-tree, which is a space- and time-efficient version of a region quadtree. Positions between snapshots are represented as logs of relative movements and compressed using Re-Pair, a grammar-based compressor. The nonterminals of this grammar are enhanced with MBR information to enable fast q…
We propose a new approach for universal lossless text compression, based on grammar compression. In the literature, a target string $T$ has been compressed as a context-free grammar $G$ in Chomsky normal form satisfying $L(G) = \{T\}$. Such a grammar is often called a \emph{straight-line program} (SLP). In this paper, we consider a probabilistic grammar $G$ that generates $T$, but not necessarily as a unique element of $L(G)$. In order to recover the original text $T$ unambiguously, we keep both the grammar $G$ and the derivation tree of $T$ from the start symbol in $G$, in compressed form. We…
Given a string $S$ of length $N$ on a fixed alphabet of $σ$ symbols, a grammar compressor produces a context-free grammar $G$ of size $n$ that generates $S$ and only $S$. In this paper we describe data structures to support the following operations on a grammar-compressed string: $\mbox{rank}_c(S,i)$ (return the number of occurrences of symbol $c$ before position $i$ in $S$); $\mbox{select}_c(S,i)$ (return the position of the $i$th occurrence of $c$ in $S$); and $\mbox{access}(S,i,j)$ (return substring $S[i,j]$). For rank and select we describe data structures of size $O(nσ\log N)$ bits that s…
Grammar-based compression is a popular and powerful approach to compressing repetitive texts but until recently its relatively poor time-space trade-offs during real-life construction made it impractical for truly massive datasets such as genomic databases. In a recent paper (SPIRE 2019) we showed how simple pre-processing can dramatically improve those trade-offs, and in this paper we turn our attention to one of the features that make grammar-based compression so attractive: the possibility of supporting fast random access. This is an essential primitive in many algorithms that process gramm…
Grammar-based compression, where one replaces a long string by a small context-free grammar that generates the string, is a simple and powerful paradigm that captures many popular compression schemes. Given a grammar, the random access problem is to compactly represent the grammar while supporting random access, that is, given a position in the original uncompressed string report the character at that position. In this paper we study the random access problem with the finger search property, that is, the time for a random access query should depend on the distance between a specified index $f$…
We solve the problems of detecting and counting various forms of regularities in a string represented as a Straight Line Program (SLP). Given an SLP of size $n$ that represents a string $s$ of length $N$, our algorithm compute all runs and squares in $s$ in $O(n^3h)$ time and $O(n^2)$ space, where $h$ is the height of the derivation tree of the SLP. We also show an algorithm to compute all gapped-palindromes in $O(n^3h + gnh\log N)$ time and $O(n^2)$ space, where $g$ is the length of the gap. The key technique of the above solution also allows us to compute the periods and covers of the string…
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 \emph{straight-line program (SLP)}, which is a context free grammar in the Chomsky normal form that derives a single string. Given an SLP $\mathcal{S}$ of size $n$ describing a text $S$ of length $N$, and an uncompressed pattern $P$ of length $m$, we present a simple $O…
The run-length compressed Burrows-Wheeler transform (RLBWT) used in conjunction with the backward search introduced in the FM index is the centerpiece of most compressed indexes working on highly-repetitive data sets like biological sequences. Compared to grammar indexes, the size of the RLBWT is often much bigger, but queries like counting the occurrences of long patterns can be done much faster than on any existing grammar index so far. In this paper, we combine the virtues of a grammar with the RLBWT by building the RLBWT on top of a special grammar based on induced suffix sorting. Our expe…
Given a string $T$ of length $N$, the goal of grammar compression is to construct a small context-free grammar generating only $T$. Among existing grammar compression methods, RePair (recursive paring) [Larsson and Moffat, 1999] is notable for achieving good compression ratios in practice. Although the original paper already achieved a time-optimal algorithm to compute the RePair grammar RePair($T$) in expected $O(N)$ time, the study to reduce its working space is still active so that it is applicable to large-scale data. In this paper, we propose the first RePair algorithm working in compress…
We consider the problem of {\em restructuring} compressed texts without explicit decompression. We present algorithms which allow conversions from compressed representations of a string $T$ produced by any grammar-based compression algorithm, to representations produced by several specific compression algorithms including LZ77, LZ78, run length encoding, and some grammar based compression algorithms. These are the first algorithms that achieve running times polynomial in the size of the compressed input and output representations of $T$. Since most of the representations we consider can achiev…
As nowadays Machine Learning (ML) techniques are generating huge data collections, the problem of how to efficiently engineer their storage and operations is becoming of paramount importance. In this article we propose a new lossless compression scheme for real-valued matrices which achieves efficient performance in terms of compression ratio and time for linear-algebra operations. Experiments show that, as a compressor, our tool is clearly superior to gzip and it is usually within 20% of xz in terms of compression ratio. In addition, our compressed format supports matrix-vector multiplication…
Grammar Boosting: A New Technique for Proving Lower Bounds for Computation over Compressed Data
本文提出了一种不依赖近似比且完全通用的Grammar Boosting技术，用于证明文法压缩数据上算法与数据结构的下界，并成功推导出多种主流压缩算法的随机访问时间下界及压缩计算的条件下界。
We consider the problem of computing the q-gram profile of a string \str of size $N$ compressed by a context-free grammar with $n$ production rules. We present an algorithm that runs in $O(N-α)$ expected time and uses $O(n+q+\kq)$ space, where $N-α\leq qn$ is the exact number of characters decompressed by the algorithm and $\kq\leq N-α$ is the number of distinct q-grams in $\str$. This simultaneously matches the current best known time bound and improves the best known space bound. Our space bound is asymptotically optimal in the sense that any algorithm storing the grammar and the q-gram prof…
We present an efficient algorithm for computing the LZ78 factorization of a text, where the text is represented as a straight line program (SLP), which is a context free grammar in the Chomsky normal form that generates a single string. Given an SLP of size $n$ representing a text $S$ of length $N$, our algorithm computes the LZ78 factorization of $T$ in $O(n\sqrt{N}+m\log N)$ time and $O(n\sqrt{N}+m)$ space, where $m$ is the number of resulting LZ78 factors. We also show how to improve the algorithm so that the $n\sqrt{N}$ term in the time and space complexities becomes either $nL$, where $L$…
Ranked MSO-enumeration over compressed words
本文研究在文法压缩字符串上，固定 MSO 查询的排名查询枚举问题，实现了线性预处理和常数延迟，并推广了 polyregular 函数的符号枚举结果。
Much research has been published about trajectory management on the ground or at the sea, but compression or indexing of flight trajectories have usually been less explored. However, air traffic management is a challenge because airspace is becoming more and more congested, and large flight data collections must be preserved and exploited for varied purposes. This paper proposes 3DGraCT, a new method for representing these flight trajectories. It extends the GraCT compact data structure to cope with a third dimension (altitude), while retaining its space/time complexities. 3DGraCT improves spa…
Computing all-vs-all MEMs in grammar-compressed text
提出一种压缩感知方法，通过构建满足fix-free属性的完全平衡语法，在不解压的情况下增量计算重复集合中所有字符串间的最大精确匹配，并探讨了其在压缩空间近似模式匹配中的应用。
Counting on General Run-Length Grammars
提出一种数据结构，能在与 grammar 大小成正比的空间内，于 O(m log^{2+ε} n) 时间内计算任意 run-length context-free grammar 压缩文本中模式的出现次数，解决了 Christiansen 等人的开放问题并增强了压缩数据计算能力。
Optimal Random Access and Conditional Lower Bounds for 2D Compressed Strings
该研究针对二维数据压缩索引的次优问题，提出首个二维文法压缩字符串的最优随机访问数据结构，证明模式匹配条件下界及基本二维查询的硬度假设，建立二维与一维压缩索引复杂度的关联。
Random Access in Grammar-Compressed Strings: Optimal Trade-Offs in Almost All Parameter Regimes
研究在语法压缩字符串中随机访问的最优折中，提出在不同参数下高效的数据结构，支持快速查询和扩展功能。
We introduce forest straight-line programs (FSLPs) as a compressed representation of unranked ordered node-labelled trees. FSLPs are based on the operations of forest algebra and generalize tree straight-line programs. We compare the succinctness of FSLPs with two other compression schemes for unranked trees: top dags and tree straight-line programs of first-child/next sibling encodings. Efficient translations between these formalisms are provided. Finally, we show that equality of unranked trees in the setting where certain symbols are associative or commutative can be tested in polynomial ti…
Right Multiplication on Grammar-Compressed Matrices: A Streaming, Memory-Bounded GPU Engine
研究在GPU内存受限场景下语法压缩矩阵右乘问题，提出基于特定有向无环图及分层语法的方法，实现流式评估，在基因型矩阵和软件遗产图上有空间优势、时间性能良好且能量较低。
Grammar compression is, next to Lempel-Ziv (LZ77) and run-length Burrows-Wheeler transform (RLBWT), one of the most flexible approaches to representing and processing highly compressible strings. The main idea is to represent a text as a context-free grammar whose language is precisely the input string. This is called a straight-line grammar (SLG). An AVL grammar, proposed by Rytter [Theor. Comput. Sci., 2003] is a type of SLG that additionally satisfies the AVL-property: the heights of parse-trees for children of every nonterminal differ by at most one. In contrast to other SLG constructions,…
We present a new algorithm for subsequence matching in grammar compressed strings. Given a grammar of size $n$ compressing a string of size $N$ and a pattern string of size $m$ over an alphabet of size $σ$, our algorithm uses $O(n+\frac{nσ}{w})$ space and $O(n+\frac{nσ}{w}+m\log N\log w\cdot occ)$ or $O(n+\frac{nσ}{w}\log w+m\log N\cdot occ)$ time. Here $w$ is the word size and $occ$ is the number of occurrences of the pattern. Our algorithm uses less space than previous algorithms and is also faster for $occ=o(\frac{n}{\log N})$ occurrences. The algorithm uses a new data structure that allows…
Dynamic Grammar-Compressed Self-Index in $δ$-Optimal Space
本文提出动态RR索引，首次在δ-最优空间内实现动态语法压缩自索引，支持高效插入删除和定位查询，优于现有动态索引。
Hardness of Frequency-Related Queries on Compressed Strings
研究压缩字符串上频率相关查询，如秩查询和符号出现查询。通过建立条件下界，证明若用特定空间结构在多对数时间内回答此类查询，将意味着布尔矩阵乘法有更快算法，还扩展了下界范围并考虑了其他相关问题。
Efficient terabyte-scale text compression via stable local consistency and parallel grammar processing
提出基于稳定局部一致性的并行文法压缩算法，实现太字节级数据高效处理，在7.9TB细菌基因组上以16线程九小时内完成压缩，体积缩小85倍。
In this paper we investigate the problem of building a static data structure that represents a string s using space close to its compressed size, and allows fast access to individual characters of s. This type of structures was investigated by the recent paper of Bille et al. Let n be the size of a context-free grammar that derives a unique string s of length L. (Note that L might be exponential in n.) Bille et al. showed a data structure that uses space O(n) and allows to query for the i-th character of s using running time O(log L). Their data structure works on a word RAM with a word size o…
Various grammar compression algorithms have been proposed in the last decade. A grammar compression is a restricted CFG deriving the string deterministically. An efficient grammar compression develops a smaller CFG by finding duplicated patterns and removing them. This process is just a frequent pattern discovery by grammatical inference. While we can get any frequent pattern in linear time using a preprocessed string, a huge working space is required for longer patterns, and the whole string must be loaded into the memory preliminarily. We propose an online algorithm approximating this proble…
LZBE: an LZ-style compressor supporting $O(\log n)$-time random access
LZBE是一种支持O(log n)时间随机访问的LZ风格压缩方法，通过结构限制实现更高效的分解和查询。
Fast and memory-efficient BWT construction of repetitive texts using Lyndon grammars
本文提出基于Lyndon直线程序从压缩表示计算BWT和eBWT的算法，在大规模重复性数据集上实现了比现有方法更快且更省内存的构建过程。
In this work we introduce a new linear time compression algorithm, called "Re-pair for Trees", which compresses ranked ordered trees using linear straight-line context-free tree grammars. Such grammars generalize straight-line context-free string grammars and allow basic tree operations, like traversal along edges, to be executed without prior decompression. Our algorithm can be considered as a generalization of the "Re-pair" algorithm developed by N. Jesper Larsson and Alistair Moffat in 2000. The latter algorithm is a dictionary-based compression algorithm for strings. We also introduce a su…
A grammar compression algorithm, called GCIS, is introduced in this work. GCIS is based on the induced suffix sorting algorithm SAIS, presented by Nong et al. in 2009. The proposed solution builds on the factorization performed by SAIS during suffix sorting. A context-free grammar is used to replace factors by non-terminals. The algorithm is then recursively applied on the shorter sequence of non-terminals. The resulting grammar is encoded by exploiting some redundancies, such as common prefixes between right-hands of rules, sorted according to SAIS. GCIS excels for its low space and time requ…
In this paper, a fully compressed pattern matching problem is studied. The compression is represented by straight-line programs (SLPs), i.e. a context-free grammars generating exactly one string; the term fully means that both the pattern and the text are given in the compressed form. The problem is approached using a recently developed technique of local recompression: the SLPs are refactored, so that substrings of the pattern and text are encoded in both SLPs in the same way. To this end, the SLPs are locally decompressed and then recompressed in a uniform way. This technique yields an O((n+…
Given a string $S$ of $n$ integers in $[0,σ)$, a range minimum query RMQ$(i, j)$ asks for the index of the smallest integer in $S[i \dots j]$. It is well known that the problem can be solved with a succinct data structure of size $2n + o(n)$ and constant query-time. In this paper we show how to preprocess $S$ into a compressed representation that allows fast range minimum queries. This allows for sublinear size data structures with logarithmic query time. The most natural approach is to use string compression and construct a data structure for answering range minimum queries directly on the co…
Grammar Index By Induced Suffix Sorting
提出一种基于诱导后缀排序的语法压缩索引，利用局部敏感解析性质，通过核心子串高效定位模式串的所有出现，时间复杂度和空间复杂度均与语法大小相关。
This paper is an extended abstract of an analysis of term rewriting where the terms in the rewrite rules as well as the term to be rewritten are compressed by a singleton tree grammar (STG). This form of compression is more general than node sharing or representing terms as dags since also partial trees (contexts) can be shared in the compression. In the first part efficient but complex algorithms for detecting applicability of a rewrite rule under STG-compression are constructed and analyzed. The second part applies these results to term rewriting sequences. The main result for submatching is…
We propose algorithms that, given the input string of length $n$ over integer alphabet of size $σ$, construct the Burrows-Wheeler transform (BWT), the permuted longest-common-prefix (PLCP) array, and the LZ77 parsing in $O(n/\log_σn+r\,{\rm polylog}\,n)$ time and working space, where $r$ is the number of runs in the BWT of the input. These are the essential components of many compressed indexes such as compressed suffix tree, FM-index, and grammar and LZ77-based indexes, but also find numerous applications in sequence analysis and data compression. The value of $r$ is a common measure of repet…
The Karp-Rabin fingerprint of a string is a type of hash value that due to its strong properties has been used in many string algorithms. In this paper we show how to construct a data structure for a string $S$ of size $N$ compressed by a context-free grammar of size $n$ that answers fingerprint queries. That is, given indices $i$ and $j$, the answer to a query is the fingerprint of the substring $S[i,j]$. We present the first O(n) space data structures that answer fingerprint queries without decompressing any characters. For Straight Line Programs (SLP) we get $O(\log N)$ query time, and for …
This paper formulates a novel problem on graphs: find the minimal subset of edges in a fully connected graph, such that the resulting graph contains all spanning trees for a set of specifed sub-graphs. This formulation is motivated by an un-supervised grammar induction problem from computational linguistics. We present a reduction to some known problems and algorithms from graph theory, provide computational complexity results, and describe an approximation algorithm.
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