My personal point of view is that with those different terms people address to the objectives for which they apply ML algorithms. Thus it is implicit that Data mining require clustering but maybe the size of the data and the purpouse it's completely different from classical IA. Ah! You forget also pattern recognition in the list! :)

You may think in this way: Data mining is the task and there are some techniques for performing it. Now the ANN is a tool we can use to implement the technique. ANN and ML both are part of Artificial Intelligence.

 Machine Learning may be the technique for performing a data mining  task.

So, roughly

If you have a data mining task

FIRST: find out some ML to do the task

second: Implement the ML process using ANN.

Dear Satya

Artificial intelligence is a set of algorithm and techniques that give the machine the ability to take some decisions based on the given input, it includes different techniques such as Fuzzy logic, Artificial neural net ANN, genetic algorithms etc.

ANN or artificial neural network is a simulation to the neurons in the brain and they need to be trained then they can be used in decision making based on the training.

best of luck

Artificial intelligence is a sub-field of computer science. It develops different techniques  allowing machines perform as humans. Machine learning is a sub-section of artificial intelligence and a lot of machine learning techniques exist.  Data mining is related to the field of data bases. Artificial intelligence works with knowledge, data mining with data

I think a lot of it has to do with the background of the researcher - computer science, signal processing, social sciences, medical/biological sciences, etc. All may end up looking at the same kind of problem, but just give it a different name, and take slightly different approaches.