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Cake day: February 17th, 2025

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  • tetris11@feddit.uktoProgrammer Humor@programming.devPeak UI Design
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    8 days ago

    hierarchical letter clustering would be my guess, or graph-based clustering using ngrams of 2-4 as nodes and maximising for connections.

    Or using an optimized Regex and printing out the DFA?

    Edit: Quick N-gram analysis (min=3, max=num letters in that month)

    R-code
    library(ngram)
    
    tmonths = c("january", "february", "march",
               "april", "may", "june", "july",
               "august", "september", "october",
               "november", "december")
    
    zzz = lapply(tmonths, function(mon){
      ng = ngram::ngram_asweka(paste(unlist(strsplit(mon, split="")), collapse=" "), min=3, max=nchar(mon))
      return(gsub(" ", "", ng))
    })
    res = sort(table(unlist(zzz)))
    res[res > 1]
    

    This gives the following 9 ngram frequencies greater than 1:

      ary   uar  uary   emb  embe ember   mbe  mber   ber 
        2     2     2     3     3     3     3     3     4 
    

    As you can see two longest most common motifs are “em-ber” and “uar-y”

    Using this I propose the following graph

    Mermaid
    stateDiagram
        direction LR
        sept --> em
        nov --> em
        dec --> em
        em --> ber
        oc --> to
        to --> ber
        feb --> uar
        uar --> y
        jan --> uar
        ju --> ne
        ju --> l
        l --> y
        ma --> r
        ma --> y
        r --> ch
        
        a --> p 
        p --> r
        r --> il
        a --> u
        u --> gust
    
    



  • wouldn’t it also be impossible to drink? The water would just seep out of any cup and find the path of least resistance to the floor

    At least with oil you can just raw dog the nozzle and squeeze it directly in, guzzling down those calories by the gallon at least until the attendant starts to run over, but by then you pull out your lighter threateningly and shake your head until he backs off again