Semantic analysis is the study of semantics, or the structure and meaning of speech. It is the job of a semantic analyst to discover grammatical patterns, the meanings of colloquial speech, and to uncover specific meanings to words in foreign languages.

1. What is semantic analysis?
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Semantic analysis is the study of semantics, or the structure and meaning of speech. It
is the job of a semantic analyst to discover grammatical patterns, the meanings of
colloquial speech, and to uncover specific meanings to words in foreign languages. In
literature, semantic analysis is used to give the work meaning by looking at it from the
writer’s point of view. The analyst examines how and why the author structured the
language of the piece as he or she did. When using semantic analysis to study dialects
and foreign languages, the analyst compares the grammatical structure and meanings
of different words to those in his or her native language. As the analyst discovers the
differences, it can help him or her understand the unfamiliar grammatical structure.
Semantic Analysis for SEO
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Semantic analysis (SA) isn’t really about synonyms and plurals (stemming) as many
folks in the biz seem to believe. If there is anyone misconception we hear the most, it is
that.
Concepts and theme — basically the problem with establishing on-page relevance is
that computers simply don’t understand the language very well (a 6th-grade level last I
heard). So they use SA to try to better understand what a page is about.
I like to use the example of the search jaguar. This could be a car, a big cat, an operating
system, a football team, etc.

2. To better understand what the page is about, they look for terms/phrases that are on
the page to categorize it. In the case of the car, we’d find terms/phrases such as auto
mechanic, engine and the animal, short hair, hunts prey and so on.
Let’s look at a search for White House. This doesn’t necessarily mean the US capital.
This might be simply to a “white” “house.” So the system would look for things such as
President of the United States. Barack Obama and so on… you get the idea.
For example, using LSA, a search engine would recognize that trips to the zoo often
include viewing wildlife and animals possibly as part of a tour.Now, conduct a search
on Google for~Zoo ~trips(the tilde is a search operator; more on this later in this
chapter). Note that the boldface words that are returned match the terms that are
italicized in the preceding paragraph. Google is setting “related” terms in boldface and
recognizing which terms frequently occur concurrently (together, on the same page, or
in close proximity) in their indexes.
Some forms of LSA are too computationally expensive. For instance, currently the
search engines are not smart enough to “learn” the way some of the newer learning
computers do at MIT. They cannot, for example, learn through their index that zebras

3. and tigers are examples of striped animals, although they may realize that stripes and
zebras are more semantically connected than stripes and ducks.Latent semantic
indexing (LSI) takes this a step further by utilizing semantic analysis to identify related
web pages. For example, the search engine may notice one page that talks about
doctors and another one that talk about physicians, and determine that there is a
relationship between the pages based on the other words in common between the
pages. As a result, the page referring to doctors may still show up in a search query that
uses the word physician instead. Search engines have been investing in these types of
technologies for many years. For example, in April 2003 Google acquiredApplied
Semantics, a company known for its semantic-text-processing technology. This
technology currently powers Google’s AdSense advertising program, and has most
likely made its way into the core search algorithms as well. For SEO purposes, this
usage opens our eyes to realise how search engines recognize the connections
between words, phrases, and ideas on the Web. As semantic connectivity becomes a
bigger part of search engine algorithms, you can expect a greater emphasis on the
theme of pages, sites, and links. It will be important going into the future to realize the
search engines’ ability to pick up on ideas and themes and recognize content, links,
and pages that doesn’t fit easily into the scheme of a website.