The application of the harmony search algorithm to the well-known problem of part-of-speech (POS) tagging is described in this paper. The harmony search algorithm involves starting from an initial state, and through a series of transformations of this state, attempting to find an optimal solution to the problem at hand. Overall, the authors did a commendable job explaining the harmony search algorithm and how it can be framed to perform POS tagging. They have also done extensive experiments on two well-known datasets to validate that their enhancements are better than other state-of-the-art systems.

The authors proposed two tweaks to the original harmony search algorithm. The first changes how the original algorithm selects transformations at each stage of its iteration. By biasing this selection toward transformations that are assessed to be better, the authors found that they were able to improve search efficiency. Further, they introduced new constraints in assessing the validity of transformations, electing to skip over those that are known to lead to bad outcomes.

There are some areas in which the authors could have done better, however. The quality of the writing in parts of the paper is patchy and sometimes borders on being incomprehensible. There are also some lapses in the accuracy of the formulas and mathematical notation. Although not a deal breaker, they require substantially more effort to parse and understand.

The authors could also have helped motivate the use of the harmony search algorithm better by explaining its significance. In particular, it is similar to genetic algorithms, and a discussion on the similarities and differences would help readers better understand the value of their proposal.

This is not a groundbreaking paper, nor is it likely to be educational if you want to find out more about the harmony search algorithm or POS tagging. However, it is definitely worth a read if you are interested in finding out how the algorithm can be applied to POS tagging and evaluate if the proposed enhancements are applicable to problems you are working on.