Compare strings of different size/length

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Michele Rizzato
Michele Rizzato 2020-12-4
评论： Stephen23 2020-12-4
I'm getting a huge headache in coding a procedure to determine similarities between two strings and so the index of the best matching into a more than 10,000 elements cell.
the i-th element of the first cell matrix is something like:
str1= 'Class music n. 12 160b'
which is the element I want to search into the other matrix. The correspondant matching element of the second matrix, e.g., is:
str2= 'Classical musical n. 12 160beats'
and so on.
I wish to find a procedure to distinguish whether this couple is the most similar with respect to all the others (others can be like
str3 = 'Techno music n. 7 120beats'
str4 = 'Rock disco n. 12 140beats'
str5 = 'Punk metal n. 18 180 beats'
or even more different).
I wish to find the index in the cell matrix where
str2
variable is, in order to manipulate it.
I've been trying several approaches, but with none of them I achieved consistent results.
Would you be able to assist me in this?
Thank you
M
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Michele Rizzato
Michele Rizzato 2020-12-4
Even if would be a long process to indentify all the abbreviations, then it will be easier to calculate the edit distance, true.
But my problem is that edit distance works with positional matching so i'd need a procedure that can identity the matching words even when put randomly into the string.
Is that possible?
Michele Rizzato
Michele Rizzato 2020-12-4
I've also tried to use FPAT for a fuzzy approach, but strangely what i get with
fpat(str1,str2)
is the following:
struct with fields:
magic: 'FPAT'
ver: '25-Oct-2004 20:49:37'
time: '04-Dec-2020 15:16:21'
runtime: 0.0053
par: [1×1 struct]
mode: 'ALL patterns'
npat: 0

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回答（2 个）

Stephen23
Stephen23 2020-12-4
Ran in:
in1 = 'Class music n. 12 160b';
in2 = {'Classical musical n. 12 160beats','Techno music n. 7 120beats','Rock disco n. 12 140beats','Punk metal n. 18 180 beats'};
rgx = {'([Cc])lass(\s+)','\d+b$'};
rpl = { '$1lassical$2','$&eats'};
tm1 = regexprep(in1,rgx,rpl);
tm2 = regexprep(in2,rgx,rpl);
edd = editDistance(tm1,tm2)
edd = 1×4
2 12 13 16
●
[~,idx] = min(edd);
in2{idx}
ans = 'Classical musical n. 12 160beats'
  2 个评论
Michele Rizzato
Michele Rizzato 2020-12-4
编辑：Michele Rizzato 2020-12-4
Thank you Stephen, this works great in the particular case, but it's not a solution i can apply to the general case. If next time i want to search for:
'Techno music n. 7 120beats'
i should write a different code
Stephen23
Stephen23 2020-12-4
Ran in:
"i should write a different code"
No, that is not the idea at all: there should be just one list of all abbreviations and their replacements (this assumes that you have this prior knowledge) which you can apply to all strings. What I showed is just a demonstration using your example data, but you will need to complete it with all abbreviations. You can then use the same code for any string that you want to match.
If the order of the words can be "random" as you wrote, then first replace the abbreviations, split the words, sort the words alphabetically (or alphanumerically), join the words, and finally measure the edit distance:
in1 = 'Class music n. 12 160b'; % string you want to match
in2 = {'Classical musical n. 12 160beats','Techno music n. 7 120beats','Rock disco n. 12 140beats','Punk metal n. 18 180 beats'};
rgx = {'([Cc])lass(\s+)', '\d+b$'};
rpl = { '$1lassical$2','$&eats'};
fun = @(s)join(sort(split(s))); % or use NATSORT (must be downloaded)
tm1 = fun(regexprep(in1,rgx,rpl));
tm2 = cellfun(fun,regexprep(in2,rgx,rpl));
edd = editDistance(tm1,tm2)
edd = 1×4
2 12 13 18
●
[~,idx] = min(edd);
in2{idx}
ans = 'Classical musical n. 12 160beats'

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Sibi
Sibi 2020-12-4
编辑：Sibi 2020-12-4
try this,
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Sibi
Sibi 2020-12-4
R='T m n. 7 120b';
code will work for this one also.
Michele Rizzato
Michele Rizzato 2020-12-4
Looks like it works great but if I start from
R='Techno alpha music n. 7 120beats'
it says that index exceed the number of array elements (6)

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