From Keyword Density to Keyword Distribution
Finally we have the Christmas Break from graduate school.
In my last Web Mining Course lecture before the Christmas Break, I tried to explain to students the importance of incorporating word spacing in information retrieval algorithms and in document relevance assessments. I explained why ideas like SEOs’s keyword density (KD), the traditional local term weight model known as FREQ (Term Count) and used in early papers on Vector Space and LSI models, and the likes are poor estimators of document relevance.
Among other theoretical reasons, it was discussed that a term mentioned X times not necessarily is X times more important than other terms. In addition, KD and the term count model cannot attenuate frequencies. We then discussed several frequency attenuation models (keyword spam filters) that also work as term weight scoring models. These can dampen down the effect of abnormal repetition of terms, raise a spam flag, and do not require of any reference to KD “tales”.
We also discussed several scenarios in which one could use word distributions and co-occurrence to analyze textual information –far better than with the aforementioned “crapstimators”. For instance, word spacing can be used in encryption/steganographic algorithms to uncover hidden messages, profiling writing styles/people, imputate authorship of text, assess plagiarism, fraud, etc.
From Keyword Distribution to William Tutte’s Legacy
This morning I came across a nice biography of one of those venerable giants: the late William Tutte. Beautifully written by Dan Younger, the biography is a tribute to Tutte’s greatness. Interesting to point out in relation to word spacing theory is this portion of Young’s writing (emphasis added):
“Tutte’s great contribution was to uncover, from samples of the messages alone, the structure of the machines which generated these codes. This came about as follows. In August 1941, a German operator sent a Fish-enciphered teleprinter message of some 4000 letters from Athens to Berlin. For some reason, the message was not received properly and so it was resent. Against all guidelines, it was sent with the same setting. It was identical in content, but it differed slightly, in word spacing and punctuation. John Tiltman of Bletchley was able to use this blunder to find both the message and the obscuring string that was added to make up the enciphered message. But that seemed to be all that could be found, when Tutte was presented with the case in October.”
“Tutte began by observing the machine generated obscuring string carefully. Splitting it up into various lengths, he noticed signs of periodicity. For the first of the five teleprinter tape positions, the regularity he supposed arose from a wheel of 41 sprockets. And then at the last position, one of 23 sprockets. Over the next months, Tutte and colleagues worked out the complete internal structure, that it had twelve wheels, two for each of the five teleprinter positions, and two with an executive function. They determined the number of sprockets on each wheel, and how the advancement of the wheels was interrelated. They had completely recreated the machine without ever having seen one. Tony Sale, who first described this work in a 1997 article in New Scientist, characterized it as the “greatest intellectual feat of the whole war.”
“Knowing the structure of the enciphering machine is a necessity for code-breaking, but it is only the first step. Tutte then put himself to creating an algorithm to find from the enciphered messages the initial settings of the machine wheels. The algorithm that he created, the “Statistical Method”, looked for certain types of resonances, but it had to consider far too many possibilities to be carried out by hand. So it was that, in 1943, the electronic computer COLOSSUS was designed and built by the British Post Office. It was to run the algorithms that Tutte; and his collaborators Max Newman and Ralph Tester; developed, that COLOSSUS was created. This man-machine combination was used to break Fish codes on a regular basis throughout the remainder of the War”.
I hope you understand now the title of this post.
In today’s Web the enciphering machines are search engines, but the underlying principles driving the Search Engines War are the same.
Emphasized words should make sense to students of the Web Mining course.