Text Extraction and retrieval
显示 更早的评论
<P ID=1>
A LITTLE BLACK BIRD.
</P>
<P ID=2>
Story about a bird,
(1811)
</P>
<P ID=3>
Part 1.
</P>
As I am new to text extraction, I need help in;
采纳的回答
Akira Agata
2017-10-25
Just tried to make a script to do that. Here is the result (assuming the maximum ID = 10).
% Read your text file
fid = fopen('yourText.txt');
C = textscan(fid,'%s','TextType','string','Delimiter','\n','EndOfLine','\r\n');
C = C{1};
fclose(fid);
% 1. Count the delimiters '</P>'
idx = strfind(C,'</P>');
n = nnz(cellfun(@(x) ~isempty(x), idx));
% 2. Remove all punctuation
C2 = regexprep(C,'[.,!?:;]','');
% 3. Break the text into individual documents at each delimiter
idx2 = find(strcmp(C,'</P>'));
for kk = 1:10
str = ['<P ID=',num2str(kk),'>'];
idx_s = find(strcmp(C,str));
if ~isempty(idx_s)
idx_e = idx2(find(idx2>idx_s,1));
fileName = ['document',num2str(kk),'.txt'];
fid = fopen(fileName,'w');
fprintf(fid,'%s\r\n',C(idx_s:idx_e));
fclose(fid);
end
end
6 个评论
John
2017-10-26
John
2017-10-28
编辑：per isakson
2017-11-9
Akira Agata
2017-10-28
I don't catch your question clearly, so let me clarify some points.
If my understanding is correct, what you want to do is:
(1) Count the total number of words in your original text file without counting the '<P ID=**>' and '</P>'
(2) Count the total number of distinct words
(3) Find the number of times each word is used in the original text
Is my understanding correct?
Akira Agata
2017-10-30
编辑：Akira Agata
2017-10-30
Thanks for your reply. I've just made a script to do the items 1~3, as follows. I hope this will help you somehow.
Regarding your last question ("count the number of documents each word appear in"), I think you can do that by combining the following script with my previous one.
% Read your text file
fid = fopen('yourText.txt');
C = textscan(fid,'%s','TextType','string','Delimiter','\n','EndOfLine','\r\n');
C = C{1};
fclose(fid);
C = regexprep(C,'<[\w \=\/]+>',''); % Remove tags
C = regexprep(C,'[.,!?:;()]',''); % Remove punctuation and brackets
C = regexprep(C,'[0-9]+',''); % Remove numbers
C = lower(C); % Convert to lower case
% Extract every words
words = regexp(C,'[a-z\-]+','match');
words = [words{:}];
% (1) Count total number of words
numOfWords = numel(words); % --> 9
% (2) Count the total number of distinct words
numOfDistWords = numel(unique(words)); % --> 7
% (3) Find the number of times each word is used in the original text
wordList = unique(words);
wordCount = arrayfun(@(x) nnz(strcmp(x,words)), wordList);
% Show the result
figure
bar(wordCount)
xticklabels(wordList)
John
2017-11-7
更多回答（2 个）
Cedric
2017-10-26
Here is another approach based on pattern matching:
>> data = regexp(fileread('data.txt'), '(?<=<P[^>]+>\s*)[\w ]+', 'match' )
data =
1×3 cell array
{'A LITTLE BLACK BIRD'} {'Story about a bird'} {'Part 1'}
if you don't need the IDs (e.g. if in any case they will go from 1 to the number of P tags), you are done.
If you needed the IDs, you could get both IDs and content as follows:
>> data = regexp(fileread('data.txt'), '<P ID=(\d+)>\s*([\w ]+)', 'tokens' ) ;
data = vertcat( data{:} ) ;
ids = str2double( data(:,1) )
data = data(:,2)
ids =
1
2
3
data =
3×1 cell array
{'A LITTLE BLACK BIRD'}
{'Story about a bird' }
{'Part 1' }
6 个评论
John
2017-10-28
data = regexp( lower( fileread( 'data.txt' )), '(?<=<p[^>]+>\s*)[^<]+', 'match' ) ;
data = regexp( data, '[a-z\-]+', 'match' ) ;
allWords = [data{:}] ;
[allUniqueWords, ~, ic] = unique( allWords ) ;
counts = accumarray( ic, 1 ) ;
After running this, you'll have all words in the allWords cell array (so numel(allWords) is the total number of words), a list of unique words in allUniqueWords (so numel(allUniqueWords) is the number of unique words), and a count of occurrence of unique words in counts.
MATLAB R2017b has a text analytics toolbox that may do this better, but I am not using it. Maybe Akira is and can develop on this. Now I think that your best option is learning the basics and studying well Akira's solution, which is the most natural approach using MATLAB base features. Mine relies more on pattern matching; while it is fairly concise, it will not teach you MATLAB to spend hours understanding regular expressions.
John
2017-10-31
Cedric
2017-10-31
My pleasure!
John
2017-11-7
If you have a count per document, finding the number of documents a keyword is in is easy:
counts = [7, 0 ,3] ;
hasKey = counts > 0 ; % [1,0,1]
nDocs = sum( hasKey ) ; % 2
Christopher Creutzig
2017-11-2
编辑：Christopher Creutzig
2017-11-2
It's probably easiest to split the text and then check the number of splits created to count, using string functions:
str = extractFileText('file.txt');
paras = split(str,"</P>");
paras(end) = []; % the split left an empty last entry
paras = extractAfter(paras,">") % Drop the "<P ID=n>" from the beginning
Then, numel(paras) will give you the number of </P>.
If you do not have extractFileText, calling string(fileread('file.txt')) should work just fine, too.
In one of the comments, you indicated you also need to count the frequency of words in documents. That is what bagOfWords is for:
tdoc = tokenizedDocument(lower(paras));
bag = bagOfWords(tdoc)
bag =
bagOfWords with 13 words and 3 documents:
a little black bird . …
1 1 1 1 1
1 0 0 1 0
…
2 个评论
John
2017-11-7
shilpa patil
2019-9-23
编辑：shilpa patil
2019-9-23
how to rewrite the above code for a document image
instead of text file
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