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S Apr 14, 2018 at 20:42 history bounty ended Stefan Haustein
S Apr 14, 2018 at 20:42 history notice removed Stefan Haustein
Apr 14, 2018 at 11:51 answer added j_random_hacker timeline score: 3
Apr 14, 2018 at 0:03 comment added Albert Hendriks For those wondering about the complexities: $m$ and $n$ are the lengths of the input strings and $s$ is the actual edit distance, so it is included in the complexity. The cost of each edit is considered 1 but is probably irrelevant for calculating this distance (the number of edits $s$).
S Apr 13, 2018 at 14:41 history bounty started Stefan Haustein
S Apr 13, 2018 at 14:41 history notice added Stefan Haustein Draw attention
Jan 6, 2016 at 11:03 history edited Kaveh CC BY-SA 3.0
added 180 characters in body
Jul 27, 2015 at 10:54 history edited user362178 CC BY-SA 3.0
Formal question
Jul 27, 2015 at 10:06 comment added user362178 Yes, in this case the large alphabet is made up of database indexes and the "strings", s and t, are lists containing these indexes.
Jul 27, 2015 at 8:53 comment added D.W. I suspect the question is: How to compute the edit distance between $s,t$, where $s,t \in \Sigma^*$ are strings over some very large alphabet $\Sigma$, and we're guaranteed that no letter appears twice in $s$ or in $t$ (the OP represents each string as a list of letters, i.e., a list of elements). But this needs confirmation.
Jul 27, 2015 at 6:24 comment added Raphael What is your question now; how to speed up pairwise edit distance, or how to speed up computing all pairwise distances of a list of strings?
Jul 27, 2015 at 6:23 history edited Raphael
edited tags
Jul 26, 2015 at 23:35 history tweeted twitter.com/#!/StackCompSci/status/625449369433677825
Jul 26, 2015 at 20:00 review First posts
Jul 27, 2015 at 11:01
Jul 26, 2015 at 19:55 history asked user362178 CC BY-SA 3.0