# Compare strings of different size/length

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Michele Rizzato on 4 Dec 2020
Commented: Stephen23 on 4 Dec 2020
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
Michele Rizzato on 4 Dec 2020
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

Stephen23 on 4 Dec 2020
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 CommentsShowHide 1 older comment
Stephen23 on 4 Dec 2020
"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'};
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'

Sibi on 4 Dec 2020
Edited: Sibi on 4 Dec 2020
try this,
Michele Rizzato on 4 Dec 2020
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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