counting most commonly used words across thousands of text files using Octave - struct

Question

I've accumulated a list of over 10,000 text files in Octave. I've got a function which cleans up the contents of each files, normalizing things in various ways (lowercase, reducing repeated whitespace, etc). I'd like to distill from all these files a list of words that appear in at least 100 files. I'm not at all familiar with Octave data structs or cell arrays or the Octave sorting functions, and was hoping someone could help me understand how to:
initialize an appropriate data structure (word_appearances) to count how many emails contain a particular word
loop thru the unique words that appear in an email string and increment for each of those words the count I'm tracking in word_appearances -- ideally we'd ignore words less than two chars in length and also exclude a short list of stop_words.
reduce word_appearances to only contain words that appear some number of times, e.g, min_appearances=100 times.
sort the words in word_appearances alphabetically and either export this as a .MAT file or as a CSV file like so:
1 aardvark
2 albatross
etc.
I currently have this code to loop through my files one by one:
for i = 1:total_files
filename = char(files{i}(1));
printf("processing %s\n", filename);
file_contents = jPreProcessFile(readFile(filename))
endfor
Note that the file_contents that comes back is pretty clean -- usually just a bunch of words, some repeated, separated by single spaces like so:
email market if done right is both highli effect and amazingli cost effect ok it can be downright profit if done right imagin send your sale letter to on million two million ten million or more prospect dure the night then wake up to sale order ring phone and an inbox full of freshli qualifi lead we ve been in the email busi for over seven year now our list ar larg current and deliver we have more server and bandwidth than we current need that s why we re send you thi note we d like to help you make your email market program more robust and profit pleas give us permiss to call you with a propos custom tailor to your busi just fill out thi form to get start name email address phone number url or web address i think you ll be delight with the bottom line result we ll deliv to your compani click here emailaddr thank you remov request click here emailaddr licatdcknjhyynfrwgwyyeuwbnrqcbh
Obviously, I need to create the word_appearances data structure such that each element in it specifies a word and how many files have contained that word so far. My primary point of confusion is what sort of data structure word_appearances should be, how I would search this data structure to see if some new word is already in it, and if found, increment its count, otherwise add a new element to word_appearances with count=1.

Answer 1

Octave has containers.Map to hold key-value pairs. This is the simple usage:
% initialize map
m = containers.Map('KeyType', 'char', 'ValueType', 'int32');
% check if it has a word
word = 'hello';
if !m.isKey(word)
m(word) = 1;
endif
% increment existing values
m(word) += 1;
This is one way to extract most frequent words from a map like the one above:
counts = m.values;
[sorted_counts, indices] = sort(cell2mat(counts));
top10_indices = indices(end:-1:end-9);
top10_words = m.keys(top10_indices);
I must warn you though, Octave may be pretty slow at this task, considering that you have thousands of files. Use it only if running time isn't that important for you.