OVT-MLCS: An Online Visual Tool for MLCS Mining from Long or Big Sequences

arXiv:2604.13037v1 Announce Type: cross
Abstract: Mining multiple longest common subsequences (textitMLCS) from a set of sequences of three or more over a finite alphabet $Sigma$ (a classical NP-hard problem) is an important task in a wide variety of application fields. Unfortunately, there is still no exact textitMLCS algorithm/tool that can handle long (length $ge$ 1,000) or big (length $ge$ 10,000) sequences, which seriously hinders the development and utilization of massive long or big sequences from various application fields today. To address the challenge, we first propose a novel key point-based textitMLCS algorithm for mining big sequences, called textitKP-MLCS, and then present a new method, which can compactly represent all mined textitMLCSs and quickly reveal common patterns among them. Furthermore, by introducing some new techniques, e.g., real-time graphic visualization and serialization, we have developed a new online visual textitMLCS mining tool, called OVT-MLCS. OVT-MLCS demonstrates that it not only enables effective online mining, storing, and downloading of textitMLCSs in the form of graphs and text from long or big sequences with a scale of 3 to 5000 but also provides user-friendly interactive functions to facilitate inspection and analysis of the mined textitMLCSs. We believe that the functions provided by OVT-MLCS will promote stronger and wider applications of textitMLCS.