We propose an interactive approach for post-processing serial episodes mined from sequential data, i. e. time-stamped sequences of events. The strength of the approach rests upon an interactive interpretation that relies on a web interface featuring various tools for observing, sorting and filtering the mined episodes. Features of the approach include interestingness measures, interactive visualization of episode occurrences in the mined event sequence, and an automatic filtering mechanism that remove episodes depending on the analyst's previous actions. We report experiments that show the advantages and limits of this approach in the domain of melodic analysis.