A branch and bound irredundant graph algorithm for large-scale MLCS problems
•Design a branch and bound strategy for identifying non-contributed points and non-longest paths.•Construct a much smaller DAG than those constructed by the existing algorithms.•Design a strategy for deleting points in the Hash table timely.•Propose a new data structure for storing Small-DAG to avoi...
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| Vydáno v: | Pattern recognition Ročník 119; s. 108059 |
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01.11.2021
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| ISSN: | 0031-3203, 1873-5142 |
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| Abstract | •Design a branch and bound strategy for identifying non-contributed points and non-longest paths.•Construct a much smaller DAG than those constructed by the existing algorithms.•Design a strategy for deleting points in the Hash table timely.•Propose a new data structure for storing Small-DAG to avoid topological sorting.•Propose a new algorithm for larger-scale MLCS problems with lower time and space cost.
Finding the multiple longest common subsequences (MLCS) among many long sequences (i.e., the large scale MLCS problem) has many important applications, such as gene alignment, disease diagnosis, and documents similarity check, etc. It is an NP-hard problem (Maier et al., 1978). The key bottle neck of this problem is that the existing state-of-the-art algorithms must construct a huge graph (called direct acyclic graph, briefly DAG), and the computer usually has no enough space to store and handle this graph. Thus the existing algorithms cannot solve the large scale MLCS problem. In order to quickly solve the large-scale MLCS problem within limited computer resources, this paper therefore proposes a branch and bound irredundant graph algorithm called Big-MLCS, which constructs a much smaller DAG (called Small-DAG) than the existing algorithms do by a branch and bound method, and designs a new data structure to efficiently store and handle Small-DAG. By these schemes, Big-MLCS is more efficient than the existing algorithms. Also, we compare the proposed algorithm with two state-of-the-art algorithms through the experiments, and the results show that the proposed algorithm outperforms the compared algorithms and is more suitable to large-scale MLCS problems. |
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| AbstractList | •Design a branch and bound strategy for identifying non-contributed points and non-longest paths.•Construct a much smaller DAG than those constructed by the existing algorithms.•Design a strategy for deleting points in the Hash table timely.•Propose a new data structure for storing Small-DAG to avoid topological sorting.•Propose a new algorithm for larger-scale MLCS problems with lower time and space cost.
Finding the multiple longest common subsequences (MLCS) among many long sequences (i.e., the large scale MLCS problem) has many important applications, such as gene alignment, disease diagnosis, and documents similarity check, etc. It is an NP-hard problem (Maier et al., 1978). The key bottle neck of this problem is that the existing state-of-the-art algorithms must construct a huge graph (called direct acyclic graph, briefly DAG), and the computer usually has no enough space to store and handle this graph. Thus the existing algorithms cannot solve the large scale MLCS problem. In order to quickly solve the large-scale MLCS problem within limited computer resources, this paper therefore proposes a branch and bound irredundant graph algorithm called Big-MLCS, which constructs a much smaller DAG (called Small-DAG) than the existing algorithms do by a branch and bound method, and designs a new data structure to efficiently store and handle Small-DAG. By these schemes, Big-MLCS is more efficient than the existing algorithms. Also, we compare the proposed algorithm with two state-of-the-art algorithms through the experiments, and the results show that the proposed algorithm outperforms the compared algorithms and is more suitable to large-scale MLCS problems. |
| ArticleNumber | 108059 |
| Author | Wang, Yuping Wang, Chunyang Cheung, Yiuming |
| Author_xml | – sequence: 1 givenname: Chunyang surname: Wang fullname: Wang, Chunyang email: 867174762@qq.com organization: School of Computer Science and Technology, Xidian University, Xian, Shaanxi, China – sequence: 2 givenname: Yuping surname: Wang fullname: Wang, Yuping email: ywang@xidian.edu.cn organization: School of Computer Science and Technology, Xidian University, Xian, Shaanxi, China – sequence: 3 givenname: Yiuming surname: Cheung fullname: Cheung, Yiuming email: ymc@comp.hkbu.edu.hk organization: Department of Computer Science, Hong Kong Baptist University, Hong Kong SAR, China |
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| Cites_doi | 10.1093/bioinformatics/btaa175 10.1016/j.patcog.2020.107516 10.1038/nmeth1156 10.1109/TPDS.2012.202 10.1016/j.cor.2009.02.005 10.1093/bioinformatics/btz725 10.1016/0304-3975(92)90132-Y 10.1038/d41586-020-00845-4 10.1109/TKDE.2014.2304464 10.1109/TKDE.2010.123 10.1016/j.patcog.2005.11.012 10.1016/j.parco.2019.102598 10.1080/10556789808805713 10.1145/322063.322075 10.1162/evco_a_00204 10.1145/359581.359603 10.1016/j.cell.2017.01.030 10.1016/j.patcog.2006.02.026 10.1109/TBME.2014.2299772 10.1145/322033.322044 10.1016/j.patcog.2020.107385 |
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| Title | A branch and bound irredundant graph algorithm for large-scale MLCS problems |
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