With all the hoopla about latent dirichlet allocation (LDA) optimization the past few weeks I decided to run a few test using SEOmoz’s LDA Topics Tool a bit. I checked a page on one of our sites that has zero incoming links and ranks #1 for the broad phrase search term “grunge boots”.
The results – 49% 55% 53% 57% 51% 56% 54% 54% 51% 55% for an average of 53.5% relevance between topics for the keyword and topics for the page. The page tested is a simple bookmark with >150 words of content that links to the original content and should not rank #1 for such a competitive search phrase.
Our Take on LDA – Latent Dirichlet Allocation
So, a little over a week ago SEOmoz put out some information on something they call LDA, or Latent Dirichlet Allocation. Some SEO people seem to think this is a game changer…well it’s not. In fact, the concept is nothing new, …
LDA – Is On-Page Optimization the SEO Secret?
“Latent Dirichlet Allocation (Blei et al, 2003) is a powerful learning algorithm for automatically and jointly clustering words into “topics” and documents into mixtures of topics. It has been successfully applied to model change in …
The Relationship Between Latent Dirichlet Allocation and Google …
SEOMoz and their research on Google’s use of Latent Dirichlet Allocation (LDA), summarized for the rest of us.
Latent Dirichlet Allocation (LDA) Correlations Clarified
Furthermore, Latent Dirichlet Allocation does not conform with Google’s primary goal of serving the most relevant result to a query. LDA is an extension of the classic “bag of words” concept that ignores word order and proximity — both …
So with no inbound links to our test page and competitors apparently doing a lousy job of optimizing for our targeted phrase LDA must be at work here?
