Sounds interesting, but theoretical. Any practical applications? I'm guessing it has some purpose on dealing with long string sequences, like genome sequencing?
Something like that + data compression. If you have some data type mapped to a sequence of symbols, WT can speed up search in it. Please also note it is not a complete full text search index (like ones used in genome sequencing). It is a rank/select dictionary.
Sounds interesting, but theoretical. Any practical applications? I'm guessing it has some purpose on dealing with long string sequences, like genome sequencing?
From what I understand, it is useful for storing compressed data and querying it without decompression.
Range queries allow for full-text search, for example.
Something like that + data compression. If you have some data type mapped to a sequence of symbols, WT can speed up search in it. Please also note it is not a complete full text search index (like ones used in genome sequencing). It is a rank/select dictionary.
I believe he's doing full text search on this by running Burrows-Wheeler on the data first. See here for more details:
I started reimplementing all of this in Go about a year ago, but moved onto other stuff before I finished.
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http://proceedings.spiedigitallibrary.org/mobile/proceeding....
I would love to see more algorithms from the signals intelligence field. Any recommendations?