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davidm1729

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Hi, I'm one of the authors of the post

Thanks for pointing us to CLMUL, I'm not familiar with these kind of multiplications, but, converting the quote bitmask to a quoted bitmask would certainly make it faster. With this new bitmask, we could negate it and AND it with the newline mask, generating a mask of newlines that are not inside quotes. Getting the last newline then would be a simple CLZ of that mask. And there wouldn't be a need to resort to byte to byte processing.

In our tests, going byte to byte for more iterations to keep the alignment when hitting the "else case" performed worse than making the unaligned loads, but as you say "just use CLMUL" (as all loads will be aligned) :D

Thank you so much!

What do you mean about having a key?

a way to jump to a genre or theme

Yes! That's a good idea!

I'm also thinking about personalized visualizations based on your favorite books, maybe this could make it more shareable on social networks in order to get traction.

Thank you!

Some sites will show you "other users also saw..." information. This is a very raw form of similarity, but a good similarity score can be computed from that data. There is no metadata involved at all right now.

I discovered a few books that I loved on Twitter a few months ago by pure luck, and I find it weird that in 2020 we didn't have more than mouth to mouth, bestseller lists, and "you may also like" to come upon some of these gems.

The site is quite self-explanatory, a large interactive map with more than 100,000 books placed and colored by their similarity. Right now, it's completely based on an algorithm, and things like being written by the same author do not directly affect position or color.

Probably the most interesting feature, apart from the map, is that when clicking on a book similar books will be highlighted based on that. However, there are other features like the ability to create your own lists.

Any feedback will be appreciated. Thank you!