customizable crm software

CRM114 is a program based upon a statistical approach for filtering email spam. While others have done statistical Bayesian filtering based upon the frequency of single word occurrences in email, CRM114 achieves a higher rate of spam recognition through creating hits based upon phrases up to five words in length. These phrases are used to form a hidden Markov model of the incoming texts. With this additional contextual recognition, it is one of the more accurate spam filters available. The author claims recognition rates as high as 99.87%. CRM114's classifier can also be switched to use Lightstone's Winnow algorithm, character-by-character correlation, or other more experimental classifiers.

As an example of pattern recognition crm customizable software software, CRM114 is a good example of machine learning accomplished with a reasonably simple algorithm. Source code in C is available through the external link.

At a deeper level, CRM114 is also a string pattern matching language, similar to grep or even Perl; although it is Turing complete it is highly tuned for matching text, and even a simple (recursive) definition of the factorial takes almost ten lines, looking much like line noise to the uninitiated. Used in this manner, it may be used for many other applications aside from detecting spam. CRM114 uses the TRE approximate-match customizable crm software regex engine, so it's possible to write programs that do not depend on absolutely identical strings matching to function correctly.

The name CRM114 is taken from the movie Dr. Strangelove or: How I Learned to Stop Worrying and Love the Bomb. The CRM-114 discriminator was designed to not receive messages unless they were proceeded by the correct 3-digit code.

External links

• The CRM114 home page on SourceForge
  
• The TRE approximate web based customizable crm software regex matcher homepage