Google is constantly looking at ways of improving the quality of the results it delivers, and ensuring that returned pages are of high relevance to the users query is obviously one of the most helpful ways in which this objective can be acheived. Most people are avawre of keyword proximity and density, the way that search engines look at the density and positioning of a given keyword or search phrase throughout a pages content in order to determine what queries that page would be relevant to, but in this article we are going to to take a look at how Google views lists and ordered text, and in particular, how semantic closeness is calculated for keywords used throughout the list.
In orthodox text format the semantic closeness of a given keyword can be calculated by counting the words in between each usage, however the fact that certain html formatting such as lists are read in a slightly different manner, means that this method is rather inaccurate.
How Is Keyword Semantic Closeness In Lists And Structured Text Calculated? Imagine the below is an unordered list on an otherwise blank webpage, With SEO Services as the pages header, if you applied the normal methodology of calculating semantic closeness to the below list you would be lead to assume that Google would see the page as being more relevant to a query for “Cheap SEO Services” than for a query based on the search phrase “affordable SEO Services”, however, you would be mistaken. Because the phrase SEO Services appears in the pages header tag and the keywords “cheap” “affordable” “effective” and “pay on results” are contained within the structure of an unordered list, Google will actually attribute the same semantic closeness to all of the keywords in the list to those in the pages header tag.
SEO Services
Cheap
Affordable
Effective
Pay On Results
This revelation has clear benefits to offer those who know about it, often when optimising a page for several similar keywords (think of sites targetting several local towns and villages, but offering the same services to each) the use of a structured list or a simular method of creating structured text would present a good opportunity for gaining good density and semantic closeness of important keywords without the need for unnecessary repetitions, this means that the optimised page will have a more organic appearance with the end result of improving the quality of content whilst still maintaining a high level of search engine optimisation.
The ability of Google to accurately attribute indentical semantic closeness to keywords included in the above list relies upon the search engine analysing html structures such as header tags, titles, bold and strong text, aswell as larger sized text which could be considered as emphasized, with nested tables, line breaks and divs all being recognised as a technique of creating lists, or more correctly, ordered structures of text.
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