Camille Thomas Barkho

Thank you very much Xitten for your feedback. In fact, what we are trying to achieve here is exactly what you mentioned. Anyway, we need to come up with the algorithm that combines maybe characters into their codes and at the time groups them into phonetic families (but this would need cultural phonetic classification - example: CH is equivalent to K phonetically in some cultures while it is equivalent to SH in other cultures). We have so far decided to use binary values (base 2) for storage of codes and calculations. Our tests are so far acceptable, but we still think we need more. Appreciate further brainstorm or ideas.

Nearness means something like: The word "school" and the word "Skool" might be 70% near or alike.

Thank you all for your responses. Our goal is to create a numeric value for any word and so that we will be able to compare the calculated values of words to other calculated values of other words to get the nearness of the two words. We are thinking of using something like bitwise operations to do the comparison. We will not surely go into technologies like phonetic or Fuzzy word match due to their slowness.

We are trying to develop an algorithm to calculate a unique numeric value for any English word. Example: School = 675237652376523 etc...