Hi moin khan,
I understand that while working on large-scale text mining in MATLAB, the goal is to:
- Process large text files to find unique words and their frequencies.
- Visually represent those word frequencies, there are thousands of unique words.
To efficiently process large text data in MATLAB:
Step 1: Read large files
Use memory-efficient reading using fileread or fopen and fscanf.
textData = fileread('largeTextFile.txt'); % Suitable for moderately large files
For very large files, prefer reading in chunks:
fid = fopen('largeTextFile.txt','r');
while ~feof(fid)
line = fgetl(fid);
% process line
end
fclose(fid);
Step 2: Tokenize text and clean it (optional but preferred)
Break the text into words, convert to lowercase, remove punctuation, etc.
cleanedText = lower(regexprep(textData, '[^\w\s]', '')); % remove punctuation
words = split(cleanedText); % tokenize
words = words(~cellfun('isempty',words)); % remove empty strings
Step 3: Count word frequencies
Use “unique” and “accumarray” functions OR “tabulate” function.
words = {'cat', 'dog', 'cat', 'bird', 'dog', 'cat'};
[uniqueWords, ~, idx] = unique(words);
counts = accumarray(idx, 1);
OR
words = {'cat', 'dog', 'cat', 'bird', 'dog', 'cat'};
T = tabulate(words)
Step 4: Visualize word frequencies using word cloud
Ideal to create a word cloud chart for hundreds or thousands of words.
wordcloud(uniqueWords, counts);
Please refer to the following documentation links for more information:
Hope this is helpful!
