SEO Changes With Latent Semantic Indexing (LSI)
The search engine optimization (SEO)
industry continues to grow everyday. In just the past three years, SEO
spending has increased in the neighborhood of 400%, and this trend is
forecasted to increase even more in the near future. This year alone,
over $1 trillion will be allocated to online marketing efforts.
Yet while search engine optimizers (SEO's) have continued to use many
of the same methods to increase the visibility and positioning of their
clients' websites in search results, the search engines themselves have
continued their evolution. Now SEO's must do the same in order to keep
up with the constantly evolving search engine algorithms of Google,
Yahoo, MSN, and a number of others.
Within the past year, many companies have no doubt noticed large
relevancy fluctuations in the search engine rankings. While most SEO's
keep scratching their heads and wondering what happened, others
research and test to identify the cause of these changes. Then they use
these findings to alter their online optimization strategies. But just how have these algorithms evolved? More importantly, what can we as SEO's do to retain top positioning?
One reason for this shuffling of results has been attributed to the inclusion of latent semantic indexing (LSI)
technology into the search engine algorithms. Google, in fact,
implemented LSI into its algorithm a few years ago and has continued to
use it since.
But what is LSI and how does it affect page rank? LSI is a system that
allows search engines to identify what a page is about beyond matching
the specific search query text. In other words, LSI looks for word
relationships within page content, just like a human being would do. It
determines the keywords of a page and then looks for related words that
are semantically close. Therefore, LSI grants related words within page
content a higher importance and value, while lowering the value of
pages that only contain specific keywords and lack related terms.
Yet while LSI technologies don't understand the meaning of any of these
words, the phrase relationships they identify between words are a major
determinant of search engine positioning. For example, a page about
McDonald's will naturally contain terms such as "hamburgers" or "Happy
Meals." For this reason, pages that target a range of related keywords
within the page content often have higher and more stable rankings for
their primary keywords.
But how do we know what words or phrases Google would consider to be
related? The best way to discover these semantic relationships is to
perform a search of Google with the tilde (~) character in front of
your query. For example, type "~hamburgers" into the search box and
Google will return pages with bolded related terms. A search for
"~hamburgers" returned the related terms "fast food," "ground beef,"
"burger," and even "fast food restaurant." Thus, Google expects to see
related words like these within the contextual content of a page
targeting the term "hamburger."
As you can see, when performing search engine optimization, it is
advantageous to error on the side of too much information than not
enough due to the fact that LSI expects to see related words and
phrases.
This is especially true because Google uses LSI to evaluate the
relevancy of your website's link profile. This means that Google
identifies how relevant each of your external and internal links are to
your keywords and website as a whole. This fact is another great reason
to mix the anchor text of your links. If all your links are based
around a particular phrase and never mention any related or similar
phrases, your site's ranking will suffer thanks to Google's LSI
algorithm.
As search engine algorithms continue to evolve and come ever closer to
mimicing human behavior in order to return the most relevant results,
we as SEO's must do our best to present page content in a way that is
most useful to users.
The power of latent semantic indexing to identify relationships between
words, within content, and even between pages is changing the way
search engines determine relevancy results and position. As SEO's, we
must utilize the power of latent semantic indexing to diversify our
pages or we'll be forced to watch them slowly fade away.
About the Author
Nick Yorchak is an SEO expert and Search Engine Marketing Specialist at Fusionbox, a full-service Denver Internet marketing,
web design, and web development company. He can be reached at his
Fusionbox email (nyorchak@fusionbox.com) or at (303)952-7490.
|