Thank you for sharing this interesting work! I will be very interested to see how far you can push this to non-repetition-based complexity measures in future.
I’d be interested to know what kind of results your LZP algorithm gives for text prediction? I’m assuming “not great”, but to me it would be an interesting point of comparison to the algorithm you are (I guess) eventually working towards.
A couple of tiny comments: for me it would have been helpful to briefly recall what is on page 2; and there’s a typo just after it first appears (“number of mistake ”).
I haven’t tried LZP in practice, but you can guess what results to expect by looking at the size of the LZ77-compression of the text. I expect that any remotely decent text prediction algorithm would be based on stochastic process prediction. The deterministic setting is just a toy model.
Thank you for sharing this interesting work! I will be very interested to see how far you can push this to non-repetition-based complexity measures in future.
I’d be interested to know what kind of results your LZP algorithm gives for text prediction? I’m assuming “not great”, but to me it would be an interesting point of comparison to the algorithm you are (I guess) eventually working towards.
A couple of tiny comments: for me it would have been helpful to briefly recall what
I haven’t tried LZP in practice, but you can guess what results to expect by looking at the size of the LZ77-compression of the text. I expect that any remotely decent text prediction algorithm would be based on stochastic process prediction. The deterministic setting is just a toy model.
Thanks for the catch!