In SEO, one of the primary focuses that specialists take note of are keywords. Keywords are necessary for websites to rank popularly with search engines such as Google. In order for a website to have a truly effective set of keywords, a study must be made which basically involves researching how frequently people research these keywords.
Like many things in SEO, however, keyword research is essentially an educated guess – and there are many unpredictable factors that have to be discovered through trial and error. The beauty of keyword research, however, is that it is a continuous learning process in which the SEO specialist will spend dozens of hours discovering what people think of the keyword, how often they will use it in their searches as well as its relevance to the website’s overarching theme.
Looking back at the relevance of keywords
During the formative years of SEO, specialists around the world flooded their content with dozens of keywords. At the time, penalties weren’t given to these abusers simply because Google’s algorithm wasn’t up to par at the time. In simpler terms, they couldn’t determine whether or not a single document or article was filled with keywords.
Google will now penalize what we now know as keyword stuffing because keyword density is something that every SEO specialist should watch out for.
Thinking back upon the much simpler times for SEO, the number one way for ranking websites was done with keyword stuffing. This was a bad practice that was considered normal at the time and a lot of SEO specialists ranked high – and for all the wrong reasons.
Times are much harder now and it is definitely harder to rank precisely because of the fierce competition between websites and SEO specialists – and keyword stuffing is no longer on anyone’s mind.
While keyword stuffing is now considered bad practice for SEO, keywords are still important and now more than ever, the quality of the keywords you use is definitely more important and more impressive than the quantity of the keywords people used to stuff in a single document – this is where TF-IDF comes into play.
In the first place, TF-IDF means term frequency – inverse document frequency and this is mostly used in text mining and information retrieval. Basically speaking, TF-IDF is used in determining how many times a word appears in a document and how significant it is to the document.
This is important to SEO because this basically means that keywords are easier to determine and the trial and error process is made significantly easier. This may not seem like a big deal but as I’ve said many times in the past, SEO is basically a game where having knowledge is having an edge over your competition – and that’s a very big deal.
TF-IDF is the result of a lifetime of study by renowned British Computer Scientist Karen Spärck Jones. During the 1970s, Dr. Jones published a paper on the concept of inverse document frequency weighing in information retrieval and today, IDF, as part of the TF-IDF weighting method is used by many search engines as part of their internal algorithm.
Application in SEO
So how does TF*IDF work specifically in SEO? As stated above, keywords are now better if they are weighted in terms of quality instead of quantity. Having more keywords may not necessarily be a good thing because Google actively penalizes people who stuff their documents with keywords. TF-IDF is essentially the revolutionary piece that makes keyword research easier and more meaningful because each finding is supported by numerous documents that Google’s crawlers will go through. Basically speaking, TF-IDF will tell you what keywords people frequently use, how frequently it appears and how significant it is to your website’s theme.
SEO is definitely made easier with TF-IDF precisely because it is a game of knowledge and that’s precisely what it brings to the table – the knowledge of what people search for, what they want, how frequently they search for it and how meaningful it is to the people who do the searching – and that information can make your SEO easier and more convenient.
For a more detailed explanation on TF-IDF, click on this link!