Stackoverflow implemented its "Related Questions" feature by taking the title of the current question being asked and removing from it the 10,000 most common English words according to Google. The remaining words are then submitted as a fulltext search to find related questions.
How do I get such a list of the most common English words? Or most common words in other languages? Is this something I can just get off the Google website?
A word frequency list is what you want. You can also make your own, or customize one for use within a particular domain, and it is a nice way to become familiar with some good libraries. Start with some text such as discussed in this question, then try out some variants of this back-of-the-envelope script:
from nltk.stem.porter import PorterStemmer
import os
import string
from collections import defaultdict
ps = PorterStemmer()
word_count = defaultdict(int)
source_directory = '/some/dir/full/of/text'
for root, dirs, files in os.walk(source_directory):
for item in files:
current_text = os.path.join(root, item)
words = open(current_text, 'r').read().split()
for word in words:
entry = ps.stem_word(word.strip(string.punctuation).lower())
word_count[entry] += 1
results = [[word_count[i], i] for i in word_count]
print sorted(results)
This gives the following on a couple of books downloaded, re the most common words:
[2955, 'that'], [4201, 'in'], [4658, 'to'], [4689, 'a'], [6441, 'and'], [6705, 'of'], [14508, 'the']]
See what happens when you filter out the most common x y or z number from your queries, or leave them out of your text search index entirely. Also might get some interesting results if you include real world data -- for example "community" "wiki" is not likely a common word on a generic list, but on SO that obviously wouldn't be the case and you might want to exclude them.