使用Julia生成ngrams

alv*_*vas 4 zip nlp n-gram julia

要在Julia中生成单词双字母,我可以简单地压缩原始列表和删除第一个元素的列表,例如:

julia> s = split("the lazy fox jumps over the brown dog")
8-element Array{SubString{String},1}:
 "the"  
 "lazy" 
 "fox"  
 "jumps"
 "over" 
 "the"  
 "brown"
 "dog"  

julia> collect(zip(s, drop(s,1)))
7-element Array{Tuple{SubString{String},SubString{String}},1}:
 ("the","lazy")  
 ("lazy","fox")  
 ("fox","jumps") 
 ("jumps","over")
 ("over","the")  
 ("the","brown") 
 ("brown","dog") 
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要生成一个三元组,我可以使用相同的collect(zip(...))习语来获得:

julia> collect(zip(s, drop(s,1), drop(s,2)))
6-element Array{Tuple{SubString{String},SubString{String},SubString{String}},1}:
 ("the","lazy","fox")  
 ("lazy","fox","jumps")
 ("fox","jumps","over")
 ("jumps","over","the")
 ("over","the","brown")
 ("the","brown","dog") 
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但是我必须在第3个列表中手动添加以进行压缩,是否有一种惯用的方式使得我可以执行n -gram的任何顺序?

例如,我想避免这样做以提取5克:

julia> collect(zip(s, drop(s,1), drop(s,2), drop(s,3), drop(s,4)))
4-element Array{Tuple{SubString{String},SubString{String},SubString{String},SubString{String},SubString{String}},1}:
 ("the","lazy","fox","jumps","over") 
 ("lazy","fox","jumps","over","the") 
 ("fox","jumps","over","the","brown")
 ("jumps","over","the","brown","dog")
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Gni*_*muc 5

另一种方法是使用Iterators.jl's partition():

ngram(s,n) = collect(partition(s, n, 1))
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Dan*_*etz 5

通过稍微改变输出并使用SubArrays 而不是Tuples,损失很少,但可以避免分配和内存复制。如果底层单词列表是静态的,这可以且更快(在我的基准测试中也是如此)。编码:

ngram(s,n) = [view(s,i:i+n-1) for i=1:length(s)-n+1]
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和输出:

julia> ngram(s,5)
 SubString{String}["the","lazy","fox","jumps","over"] 
 SubString{String}["lazy","fox","jumps","over","the"] 
 SubString{String}["fox","jumps","over","the","brown"]
 SubString{String}["jumps","over","the","brown","dog"]

julia> ngram(s,5)[1][3]
"fox"
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对于较大的单词列表,内存要求也显着降低。

另请注意,使用生成器可以更快地处理 ngrams 并使用更少的内存,并且可能足以处理所需的处理代码(计算某些内容或传递一些哈希值)。例如,使用@Gnimuc 的解决方案而没有collectie just partition(s, n, 1)