Ink-parser-parameter optimization may be performed via parallel processing to accelerate searching for a set of optimal ink-parser parameters. Evaluators may parse pages of ink notes with different groups of parameters and may compute corresponding values for evaluation functions. Separate evaluation functions may be defined for the following types of ink-parker parsing engines: writing parser, writing/drawing classification, table detection, and list detection. A searcher may perform a grid-searching algorithm or a genetic algorithm to generate groups of parameters and may then pass the parameters to available evaluators for evaluation until evaluation-function values for a group of parameters satisfy a convergence condition.