Some SEOs, in an effort to sell something, gain credibility, or save face, will come up with all sort of theories made out of thin air about search engines. When not citing themselves, they cite each other hearsays, often through their link farms. When caught with the pants down, they will lie or edit qualifiers in their posts. Can you guess who, according to Mike Duz, wrote this?

“Some of those well in the know attribute this to latent semantic indexing, which Google has been using for a while, but recently increased its weighting”. (From the Internet Archive)”

According to Duz, this guy later changed his categorical assertion into this:

“Even if they are not using LSI, Google has likely been using other word relationship technologies for a while, but recently increased its weighting”.

Note that in this case changing the qualifier (“had” to “if”) also changes the categorically asserted facts, which is not a minor thing since flies against Credibility. Thanks, Mike.

Answer: (Aaron Wall)

What a saving face effort!

Instances of such kind of edits are not new across the Web.

We roast these folks simply because they sell search engine snake oil and lies often to promote themselves, their peers, or some kind of crap tool or service. We do this through IR knowledge. One of our goals is to warn the ethical sector of the search marketing industry about such pseudo experts.

We will hammer their myths any day of the year, which takes us to another persistent myth about how search engines work: the search exhaustivity myth.

SEOs have this idea that when a user submits a query, the system does an exhaustive search through the entire document collection or index to compute term weights and rank documents according to a particular similarity measure. Evidently these folks do not know how an inverted index works. One of the reasons (there are many) for using inverted indexes is to avoid searching through all the documents listed, present in a collection. “Jumping” and “intersecting” posting lists is one of the reasons why search engines return results so fast.

BTW, when we understand how positional inverted indexes work, the benefits of document linearization, a topic we have written on before, become clear.

How an inverted index works is a good topic for IR Watch – The Newsletter.

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