Natalie Damaso, Kyleen E Elwick, James M Robertson
Guidelines for the Analysis of DNA Barcoding/Metabarcoding Sequencing Data and Interpretation of Publicly Available Databases
Methods in molecular biology (Clifton, N.J.)
frequent sequence pattern mining excellent tool discover patterns event chains complex systems events parallel processes present often without proper labelling identify groups events related subprocess frequent sequential pattern mining applied since algorithms provide many frequent sequences make difficult interpret results necessary postprocess resulting frequent patterns available visualisation techniques allow easy access multiple properties support faster better understanding event scenarios answer issue work proposes intuitive interactive solution support task introducing three novel networkbased sequence visualisation methods reduce time information processing cognitive perspective proposed visualisation methods offer information rich easily understandable interpretation sequential pattern mining results compared usual textlike outcome pattern mining algorithms first uses confidence values transitions create weighted network second enriches adjacency matrix based confidence values similarities transitive nodes enriched matrix enables similaritybased multidimensional scaling mds projection sequences third method uses similarity measurement based overlap occurrences supporting events sequences applicability method presented industrial alarm management problem analysis clickstreams website method fully implemented python environment results show proposed methods highly applicable interactive processing frequent sequences supporting exploration inner mechanisms complex systems