This function reads the alphanumeric words (e.g. 'Finance', 'recycle', 'M16') from a plain text document (.txt) and displays the most frequently used words in the document. For example, after processing a document containing pizza recipes, I got the following output from this function:
'WORD' 'FREQ' 'REL. FREQ'
'dough' [ 170] '1.1336%'
'flour' [ 84] '0.5601%'
'oven' [ 70] '0.4668%'
'pizza' [ 49] '0.3268%'
'sauce' [ 47] '0.3134%'
'cheese' [ 39] '0.2601%'
The first column consists of the most frequently used words in this document. The second column consists of the frequency of the word (i.e. the number of times that the word appeared in the document). The last column contains the relative frequency of the word, which is simply the frequency of the word divided by the total number of words in the document. This function might be useful for statistical purposes such as analyzing the writing habits of a particular author. Please note that the words are case-sensitive, which means 'Great' and 'great' are treated as two different words.
The first input, 'filename', is simply the name of the text file. The second input, 'num', is the number of words you want to have the function display. For example, if you only want to see the top 10 most frequenly used words, simply set 'num' to 10. However, please note that this function only displays the words which were used at least twice. Therefore, if the number of words used more than once is less than the value of 'num', only those words will be displayed and you will see fewer words in the output than you specified.
The output, 'results', simply shows a table that looks like the output in the pizza recipe example described above.
HOW TO USE:
Say you want to find out the most frequenly used words in a article you found on the web. Simply copy that article and paste it into Notepad. Save the text file with whatever name you want (e.g. 'article.txt'). Then navigate to the directory containing the text file in MATLAB and type:
results = wordcount('article.txt', 10)
to see the top 10 most frequently used words in article.txt.