2011/02/22 by Yasuo Tabei, Daisuke Okanohara, Tabei, Yasuo +5
Computer Science · #Algorithms and Data Compression #Data Mining Algorithms and Applications #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Semantic Web and Ontologies #cs.DS
paper · pdf · doi:10.48550/arxiv.1102.4480
This paper is going to be published in proceedings of 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD2011)
openalex publication_date 2011/02/22 · arxiv created 2011/03/05 · arxiv updated 2011/03/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
A linear graph is a graph whose vertices are totally ordered. Biological and linguistic sequences with interactions among symbols are naturally represented as linear graphs. Examples include protein contact maps, RNA secondary structures and predicate-argument structures. Our algorithm, linear graph miner (LGM), leverages the vertex order for efficient enumeration of frequent subgraphs. Based on the reverse search principle, the pattern space is systematically traversed without expensive duplication checking. Disconnected subgraph patterns are particularly important in linear graphs due to their sequential nature. Unlike conventional graph mining algorithms detecting connected patterns only, LGM can detect disconnected patterns as well. The utility and efficiency of LGM are demonstrated in experiments on protein contact maps.