Machine Learning, a subfield of computer science, involves the development of mathematical algorithms that discover knowledge from specific data sets, and then "learn" from the data in an iterative fashion that allows predictions to be made.
Machine learning is defined as "a subfield of computer science (CS) and artificial intelligence (AI) that deals with the construction and study of systems that can learn from data, rather than follow only explicitly programmed instructions.
The major subfields of computer science include the traditional study of computer architecture, programming languages, and software development.
The authors divide the globe into three main regions and evaluate how research is conducted in 30 different subfields of Computer Science for each of the considered regions, focusing on the structural and temporal features of the network.
As an emerging subfield of computer science, data mining technologies suit this need well and have been proposed for relevant knowledge discovery in the past several years.
I'll describe burgeoning research in each of these topics and argue the need for a new subfield of computer science.
In the subfield of computer science and information science known as Knowledge Representation, the term "ontology" refers to a consensual and reusable vocabulary of identified concepts and their relationships regarding some phenomena of the world, which is made explicit in a machine-readable language.
"In the subfield of computer science and information science known as Knowledge Representation, the term 'ontology' refers to a consensual and reusable vocabulary of identified concepts and their relationships regarding some phenomena of the world, which is made explicit in a machine-readable language.
Specifically, machine learning is the subfield of computer science that is concerned with the development of software programs that provide computer systems with the ability to learn from experiences without pursuing explicitly programmed instructions that is, to teach themselves to grow and change when exposed to new data [19].
Its applications have spread to almost all areas of computer science and many other disciplines.
