arXiv subjects

Diptarama Hendrian

Publications and source records attributed to Diptarama Hendrian.

22 records · Page 2Linked to original sources

arXiv2019

Linear-Time Online Algorithm Inferring the Shortest Path from a Walk

We consider the problem of inferring an edge-labeled graph from the sequence of edge labels seen in a walk of that graph. It has been known that this problem is solvable in $O(n \log n)$ time when the targets are path or cycle graphs. This paper presents an online algorithm for the problem of this restricted case that runs in $O(n)$ time, based on Manacher's algorithm for computing all the maximal palindromes in a string.

cs.DS↗

arXiv2019

Efficient Dynamic Dictionary Matching with DAWGs and AC-automata

The dictionary matching is a task to find all occurrences of patterns in a set $D$ (called a dictionary) on a text $T$. The Aho-Corasick-automaton (AC-automaton) is a data structure which enables us to solve the dictionary matching problem in $O(d\logσ)$ preprocessing time and $O(n\logσ+occ)$ matching time, where $d$ is the total length of the patterns in $D$, $n$ is the length of the text, $σ$ is the alphabet size, and $occ$ is the total number of occurrences of all the patterns in the text. The dynamic dictionary matching is a variant where patterns may dynamically be inserted into and deleted from $D$. This problem is called semi-dynamic dictionary matching if only insertions are allowed. In this paper, we propose two efficient algorithms. For a pattern of length $m$, our first algorithm supports insertions in $O(m\logσ+\log d/\log\log d)$ time and pattern matching in $O(n\logσ+occ)$ time for the semi-dynamic setting and supports both insertions and deletions in $O(σm+\log d/\log\log d)$ time and pattern matching in $O(n(\log d/\log\log d+\logσ)+occ(\log d/\log\log d))$ time for the dynamic setting by some modifications. This algorithm is based on the directed acyclic word graph. Our second algorithm, which is based on the AC-automaton, supports insertions in $O(m\log σ+u_f+u_o)$ time for the semi-dynamic setting and supports both insertions and deletions in $O(σm+u_f+u_o)$ time for the dynamic setting, where $u_f$ and $u_o$ respectively denote the numbers of states in which the failure function and the output function need to be updated. This algorithm performs pattern matching in $O(n\logσ+occ)$ time for both settings. Our algorithm achieves optimal update time for AC-automaton based methods over constant-size alphabets, since any algorithm which explicitly maintains the AC-automaton requires $Ω(m+u_f+u_o)$ update time.

cs.DS↗

arXiv2018

Enumerating Cryptarithms Using Deterministic Finite Automata

A cryptarithm is a mathematical puzzle where given an arithmetic equation written with letters rather than numerals, a player must discover an assignment of numerals on letters that makes the equation hold true. In this paper, we propose a method to construct a DFA that accepts cryptarithms that admit (unique) solutions for each base. We implemented the method and constructed a DFA for bases $k \le 7$. Those DFAs can be used as complete catalogues of cryptarithms,whose applications include enumeration of and counting the exact numbers $G_k(n)$ of cryptarithm instances with $n$ digits that admit base-$k$ solutions. Moreover, explicit formulas for $G_2(n)$ and $G_3(n)$ are given.

cs.FL↗

arXiv2018

Fully-Online Suffix Tree and Directed Acyclic Word Graph Construction for Multiple Texts

We consider construction of the suffix tree and the directed acyclic word graph (DAWG) indexing data structures for a collection $\mathcal{T}$ of texts, where a new symbol may be appended to any text in $\mathcal{T} = \{T_1, \ldots, T_K\}$, at any time. This fully-online scenario, which arises in dynamically indexing multi-sensor data, is a natural generalization of the long solved semi-online text indexing problem, where texts $T_1, \ldots, T_{k}$ are permanently fixed before the next text $T_{k+1}$ is processed for each $1 \leq k < K$. We present fully-online algorithms that construct the suffix tree and the DAWG for $\mathcal{T}$ in $O(N \log σ)$ time and $O(N)$ space, where $N$ is the total lengths of the strings in $\mathcal{T}$ and $σ$ is their alphabet size. The standard explicit representation of the suffix tree leaf edges and some DAWG edges must be relaxed in our fully-online scenario, since too many updates on these edges are required in the worst case. Instead, we provide access to the updated suffix tree leaf edge labels and the DAWG edges to be redirected via auxiliary data structures, in $O(\log σ)$ time per added character.

cs.DS↗