in How To Reference Material by Jeffrey_Smith

Latent Semantic Indexing and SEOWhat does it take to produce a top 10 ranking? The answer is simple with SEO, just eliminate 990 other pages for the square root of relevance extracted from Pair, Sort-Based Computation and probabilistic methods for extracting relevance.

Proximity is important, hence, a keyword followed by augmenting the description with relevant synonymous keywords are strong indicators for co-occurrence, particularly when augmented by H1 continuity, bold, italic and semantic synonyms throughout the page.

Through grouping relevant on page factors by observing the rules of how search engines function, it is possible to reinforce topical semantic thresholds for content to procure higher rankings (without resorting to keyword stuffing).

Translation: Use relevant tags, synonyms and folksonomy to reinforce your pages data’s signature / footprint. As a result, spiders will elevate your relevance for key indicators.

What does this mean to you? It means, create as many tactfully overlapping algorithmic elements on a page to virtually outrank your competition (on a scale of page to page relevance score). The searcher and the searched must have continuity for the executed search term pinged as a query. However, the more prime market share your page can occupy without resorting to artificial methods of inflating relevance the better.

Be thankful that search engines can read and assemble rules based on grammar, frequency and context. All of which are contingent on language, so the rules of language supersede the algorithms prime directive (which is to seek, match and retrieve).

What are some of the things that can affect page weight for relevance? The age of content, referring co-citation of references (links) on page factors (grouping of relevant shingles and clusters a.k.a. on page SEO factors) as well as the total saturation of keyword co-occurrence within a site (authority based on the total volume of the content available).

If you are familiar with the thesaurus tool, then you can grasp the continuity of synonyms (similar words) and polysyllabic words (words that can have more than one meaning). Based on the coherence between context search engines have been programmed to identify patterns of relevance to extract theoretical and tangible correlations.

For example, if I am speaking about a “diamond” and use the words luster one meaning is extracted, if I use the word “hot-dog” or “mit” in context, then another value is assigned based on the cluster of words presented.

Even though we utilize a linear approach to gain contextual relevance when we read, search engines can use dozens of computational methods on a page (or the entire site) to extract focal points or nodes to assemble pivotal points of data that determine relevance score.

Are pages linked using a said cluster? (keyword), does the keyword appear anywhere else on the document?, in the site?, if so, how frequently does it appear and with what percentage to the total value of related and overlapping contingents?

Through this type of virtual assembly (from the data cloud / your website) this contributes to the weighting factors that flags search engines that your page has something worth sharing with others and hence adds it to the cue.

As a result, if you understand this process as a component of search and refine each page to a laser-like focus, the crowning achievement is to allow the most pertinent aspect of the page to provide overlapping continuity for rankings (which is the basis of the next exercise).

Exercise for Tweaking Titles, Descriptions and Tags with Semantic Synonyms

1 ) Start by visiting the visual thesaurus, if your page is about a specific topic (which it should be) then start with the main keyword in this tool.

2 ) From there, see how many other alternative words appear that could be supplemented in place of the original keyword. Write them down or create a column of replacement / alternative keywords in an excel file or on paper so you can use them to replace the original keyword later on.

3) Use the ~ followed by a keyword such as ~phrase in a Google search box to see which other phrases are significantly aligned with the keyword. For example, ~dog will also show bolded keywords such as pet, puppies, dog breed, etc. Look for parallels between the two tools (the thesaurus and Google). In this instance ~phrase also equates to word, and dictionary (to show the parallel of relevant keywords).

4) Now, rewrite your supporting meta description with additional alternative words gleaned from the exercise as well as sprinkle a few words throughout the document and the tags (if you are using a blog).

Without giving the farm away on this one, I will leave it up to you on how far you go with it. The idea is, produce the appropriate on page factors initially using revisions to keywords using semantic symmetry (not overusing or stuffing keywords) in tandem with internal linking (which can also use this method).

With these two tips, you can create valuable cross sections of overlapping keywords to promote an infrastructure that supports your main topic / theme of the page and your website.

By aiding the search engine from choosing your pages seed words, continuity of phrases, correlations of contextual relevance and the proper use of tags, titles and clusters, you can pull rank on many competitors who loosely overlook these measures as a valuable method for leveraging your on page assets.

This post was inspired by the brilliance of Narayanan Shivakumar and Hector Garcia-Molina from the Department of Computer Science hailing from Stanford University outlining the parameters of search and Finding near-replicas of documents on the web.  

About Jeffrey_Smith

In 2006, Jeffrey Smith founded SEO Design Solutions (An SEO Provider who now develops SEO Software for WordPress).

Jeffrey has actively been involved in internet marketing since 1995 and brings a wealth of collective experiences and marketing strategies to increase rankings, revenue and reach.

6 thoughts on “Using LSI Based Synonyms for On Page Semantic Relevance
  1. LSI is so interesting. It just shows the magnitude at which search engines are evolving. I remember reading an interesting blogpost on the basics on LSI Ever since I read this post, I have been very interested in this topic.

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