Computing minimal and maximal suffixes of a substring
We consider the problems of computing the maximal and the minimal non-empty suffixes of substrings of a longer text of length . n. For the minimal suffix problem we show that for every . τ, . 1≤τ≤logn, there exists a linear-space data structure with . O(τ) query time and . O(nlogn/τ) preprocessing time. As a sample application, we show that this data structure can be used to compute the Lyndon decomposition of any substring of the text in . O(kτ) time, where . k is the number of distinct factors in the decomposition. For the maximal suffix problem, we give a linear-space structure with . O(1) query time and . O(n) preprocessing time. In other words, we simultaneously achieve both the optimal query time and the optimal construction time. © 2015 Elsevier B.V.
We revisit the problems of computing the maximal and the minimal non-empty suffixes of a substring of a longer text of length n, introduced by Babenko, Kolesnichenko and Starikovskaya [CPM’13]. For the minimal suffix problem we show that for any 1 ≤ τ ≤ logn there exists a linear-space data structure with(τ)query time and(nlogn/τ)preprocessing time. As a sample application, we show that this data structure can be used to compute the Lyndon decomposition of any substring of the text in(kτ)time, where k is the number of distinct factors in the decomposition. For the maximal suffix problem we give a linear-space structure with(1)query time and(n)preprocessing time, i.e., we manage to achieve both the optimal query and the optimal construction time simultaneously.
Deals with the development of threads synchronizing strategies based on the creation of concurrent «flat-combining» data structures as well as research of their performance. The paper considers «flat-combining» approach and its implementation in the library libcds, the development of thread synchronization strategy and its possible implementations. The efficiency of synchronization strategies usage is researched on the example of the open source library libcds. The research revealed the strategy with the lowest operation execution time on a container and the lowest amount of CPU resources, and identifies use cases of the developed strategies. A mechanism with the developed synchronization strategy to build concurrent data structures was implemented. The implemented strategies were integrated in the cross-platform open source library libcds.
Heaps are well-studied fundamental data structures, having myriads of applications, both theoretical and practical. We consider the problem of designing a heap with an “optimal” extract-min operation. Assuming an arbitrary linear ordering of keys, a heap with n elements typically takes O(log n) time to extract the minimum. Extracting all elements faster is impossible as this would violate the Ω (nlog n) bound for comparison-based sorting. It is known, however, that is takes only O(n+ klog k) time to sort just k smallest elements out of n given, which prompts that there might be a faster heap, whose extract-min performance depends on the number of elements extracted so far. In this paper we show that this is indeed the case. We present a version of heap that performs insert in O(1) time and takes only O(log ∗ n+ log k) time to carry out the k-th extraction (where log ∗ denotes the iterated logarithm). All the above bounds are worst-case. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.
The 12th issue of LNCS Transactions on Petri Nets and Other Models of Concurrency (ToPNoC) contains revised and extended versions of a selection of the best papers from the workshops held at the 37th International Conference on Application and Theory of Petri Nets and Concurrency (Petri Nets 2016, Toruń, Poland, 19–24 June 2016), and the 16th International Conference on Application of Concurrency to System Design (ACSD 2016, Toruń, Poland, 19 – 24 June 2016). It also contains one paper submitted directly to ToPNoC.
We study the following three problems of computing generic or discriminating words for a given collection of documents. Given a pattern $P$ and a threshold $d$, we want to report (i) all longest extensions of $P$ which occur in at least $d$ documents, (ii) all shortest extensions of $P$ which occur in less than $d$ documents, and (iii) all shortest extensions of $P$ which occur only in $d$ selected documents. For these problems, we propose efficient algorithms based on suffix trees and using advanced data structure techniques. For problem (i), we propose an optimal solution with constant running time per output word.
This book constitutes the proceedings of the 21st International Symposium on String Processing and Information Retrieval, SPIRE 2014, held in Ouro Preto, Brazil, in October 2014. The 20 full and 6 short papers included in this volume were carefully reviewed and selected from 45 submissions. The papers focus not only on fundamental algorithms in string processing and information retrieval, but address also application areas such as computational biology, Web mining and recommender systems. They are organized in topical sections on compression, indexing, genome and related topics, sequences and strings, search, as well as on mining and recommending.
This book constitutes the refereed proceedings of the 23rd Annual Symposium on Combinatorial Pattern Matching, CPM 2012, held in Helsinki, Finalnd, in July 2012. The 33 revised full papers presented together with 2 invited talks were carefully reviewed and selected from 60 submissions. The papers address issues of searching and matching strings and more complicated patterns such as trees, regular expressions, graphs, point sets, and arrays. The goal is to derive non-trivial combinatorial properties of such structures and to exploit these properties in order to either achieve superior performance for the corresponding computational problems or pinpoint conditions under which searches cannot be performed efficiently. The meeting also deals with problems in computational biology, data compression and data mining, coding, information retrieval, natural language processing, and pattern recognition.
This paper presents two new approaches to solving a classical NP-hard problem of maximum clique problem (MCP), which frequently arises in the domain of information management, including design of database structures and big data processing. In our research, we are focusing on solving that problem using the paradigm of artificial neural networks. The first approach combines the artificial neuro-network paradigm and genetic programming. For boosting the convergence of the Hopfield neural network (HNN), we propose a specific design of the genetic algorithm as the selection mechanism for terms of the HNN energy function. The second approach incorporates and extends the tabu-search heuristics improving performance of network dynamics of so-called tabu machine. Introduction of a special penalty function in tabu machine facilitates better evaluation of the search space. As a result, we demonstrate the proposed approaches on well-known experimental graphs and formulate two hypotheses for further research.