Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
A Space-Bounded Anytime Algorithm for the Multiple Longest Common Subsequence Problem. |
| Συγγραφείς: |
Yang, Jiaoyun1, Xu, Yun1, Shang, Yi2, Chen, Guoliang1 |
| Πηγή: |
IEEE Transactions on Knowledge & Data Engineering. Nov2014, Vol. 26 Issue 11, p2599-2609. 11p. |
| Θεματικοί όροι: |
*Algorithms, *Problem solving, Programmable sequence controllers, Spacetime, Bounded arithmetics, Experimental design |
| Περίληψη: |
The multiple longest common subsequence (MLCS) problem, related to the identification of sequence similarity, is an important problem in many fields. As an NP-hard problem, its exact algorithms have difficulty in handling large-scale data and time- and space-efficient algorithms are required in real-world applications. To deal with time constraints, anytime algorithms have been proposed to generate good solutions with a reasonable time. However, there exists little work on space-efficient MLCS algorithms. In this paper, we formulate the MLCS problem into a graph search problem and present two space-efficient anytime MLCS algorithms, SA-MLCS and SLA-MLCS. SA-MLCS uses an iterative beam widening search strategy to reduce space usage during the iterative process of finding better solutions. Based on SA-MLCS, SLA-MLCS, a space-bounded algorithm, is developed to avoid space usage from exceeding available memory. SLA-MLCS uses a replacing strategy when SA-MLCS reaches a given space bound. Experimental results show SA-MLCS and SLA-MLCS use an order of magnitude less space and time than the state-of-the-art approximate algorithm MLCS-APP while finding better solutions. Compared to the state-of-the-art anytime algorithm Pro-MLCS, SA-MLCS and SLA-MLCS can solve an order of magnitude larger size instances. Furthermore, SLA-MLCS can find much better solutions than SA-MLCS on large size instances. [ABSTRACT FROM AUTHOR] |
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| Βάση Δεδομένων: |
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