Your curiosity indeed is to know about the topic. What is that I am talking about here? Yes, shortly that is what we will see. In the first place, we need to observe that Artificial Intelligence and Big Data truly have a functional link.
AI to become operational, the first step is the data. From these describe patterns and make logical connections. Consequently, these patterns help us to draw some coherent inferences. Put otherwise, Artificial Intelligence is possible with Large Data.
So, Big Data is Complementary to AI
From this big data, patterns emerge. Enabling us to decide how certain parameters influence the possible outcomes.
Did it make sense?
Next comes the missing link “Machine learning.”
When we talk about, Machine Learning we mean the ability of computers to combine algorithms. Then through Natural Language processors create a system that is capable of making machines perform tasks on their own.
Link ML, NLP, And AI
Artificial intelligence is a concept that involves, Computers or such systems capable of logically make decisions driven by capacity acquired through large-scale machine learning processes.
Since we are more concerned about the effects of all this technology on Search Engine Optimization, I am giving only the gist. If you want further detailed study go here
The Triad of AI, Machine Learning, And Big Data
Once you are able to understand the role of each one of them and how they complement, you would be able to better take advantage of and use it more creatively.
Therefore, it is evident that in our investigation of how artificial intelligence and big data play a role in Search engine optimization, which we are ultimately interested in as Bloggers.
Big Data The Base
If you are asking for an explanation of What is Called Big Data. The probable answer would be anything that is above 1000 GB or 1 Terabyte. For easy understanding, we say this. Strictly speaking, no clear definition is possible for Big Data.
Assume it is large enough. For comparison, a typical human brain has about data equivalent to 1petabytes (one million GB)
Suppose that we need to collect samples from say 100 people the volume of data required that we are considering. It is very large.
Data Mining The First Step
Collecting the Data itself is a very challenging task. Classified by the Source:-
- Internal Sources and
- External Sources.
Types of Data
Depending upon the basic use of the Data Collected and the statistical model deployed again we Classify it as :
- Descriptive Statistical Model
- Inferential Model
3. Computational Statistical
Descriptive Statistical Model
This model is used, as the name suggests, to find statistical parameters like
- Standard deviation,
Inferential Statistical Model
An inferential Statistical Model is basically to draw some conclusions from the data.
We use this model to get a deeper understanding of the data and to make predictions using extrapolation. That means by extending the graph generated by the data collected.
With the help of computer science, applying statistical technics, and using algorithms computers are capable of drawing inferences. The widely used application of this computational are useful in predictive modeling and in Machine Learning ( ML )
From Big Data To Machine Learning
Our first journey of ‘Marrying’ Big Data with Machine Learning is done. The process of making sense of Raw Data has magically turned into integrated learning by the Machine aka Computers.
Relation Between M L And A I
Big Data Al ML Deep Learning. Earlier we saw that Raw Data by Computational Methods could draw patterns and Inferences. However, to make more and more inferences are made in real-time there is feedback and deep learning enabled.
Connecting With SEO
That was perhaps too much technical stuff for bloggers, who are otherwise busy with, blogs, content, Traffic, and such things.
So, now I return to your pet topic -SEO.
Google PageRank & Algorithm is something people on the Internet, especially are interested in.
It is everybody’s guess that it might not affect your page rank. We are but mute spectators at best.
However, I hasten to say that SEO is directly connected with these technological advancements
Now Deep learning machine capability would certainly be able to interpret the content in the light of Keyword relevance.
Also, Estimate Information Entropy “Calculating information and entropy is a useful tool in machine learning and is used as the basis for techniques such as feature selection, building decision trees, and, more generally, fitting classification models. As such, a machine learning practitioner requires a strong understanding and intuition for information and entropy.”
We need to update our knowledge for the simple reason, it helps us be aware of the search engines looking for inside our blog.
- Your heading and sub-heading should reflect a connection with the Keyword.
- Overall content would be useful to the browser.
- Whether the browser per se would get a good user experience.
So, it implies that we should focus on our customers. And take care of them. Really, getting into their shoes, we know exactly where it pinches. By doing so, you need not worry about anything else. That should be our prime concern.
At end of the day, truly, the aim and objective of all processes of Search Engine Optimization are to find:
- How relevant the content is to the search phrase or the keyword.
- How detailed information the writer gives.
- Concepts, theories, and ideas that make the topic clear.
- Illustrative diagrams, data, sketches and audio, video clips.
Therefore it is our aim to highlight certain technological processes happening at the back-end. It is never an end itself.
You as a blogger, are familiar with the role of readability style, title tags, use of emotional words, and use of direct simple structure.
Nonetheless, search criteria are, therefore, how your audience receives and how do they react, sharing and commenting, etc.