Can Machine Learning be used for Natural Language Understanding

Question

This is based on my earlier question . Can I use machine learning algorithms to help me with understanding sentences?

(I will use a closely related example as I used in my previous question). For example, I want my algorithm/code to start a program based on what the user says. For instance, if he says "turn on the program," then the algorithm should do that. However, if the user says "turn on the car," the computer shouldn't turn on the program, obviously. (BUT how would a computer know?) I am sure there are hundreds of different ways to say "start" or "turn on the program." What I am asking is how can a computer differentiate between "program" and "car"? How can the algorithm know that in the first sentence, it has to start the program, but not in the second one? Is there a way for the algorithm to know what the sentence is talking about ?

Could I use an unsupervised learning algorithm for this, that is, one that can learn what the sentence is about?

Thanks

Answer 1

Natural language understanding is a very hard problem and many researchers are working on it. To begin with, basic Natural language understanding systems start off as rule based. You manually write down rules that will be matched against an input, and if a match is found, you fire a corresponding action. So, you restrict the format of your input and come up with rules while keeping them as general as possible. For example, instead of matching the exact statement "turn on the program", you can have a rule such as: unless the word "program" occurs in the command, don't start the program, OR ignore every sentence unless it contains "program". And then, combine your rules to develop more complex "understanding". How to write/represent rules is another tough problem. You can start off with Regular Expressions.

Regarding various ways of expressing the action of "Start"ing something, you are going to look at Synonyms for "start", eg "begin". This can be obtained from a thesaurus and a commonly used resource for such tasks is WordNet

You need to figure out what information do you exactly want to extract from the sentence. Most natural language techniques are task specific, there isn't be a general one-size-fits-all natural language understanding tool.

Answer 2

no machine learning algorithms can learn without enough information input. If there are enough information about a car versus a program, then the learning algorithms may differentiate them. Machine learning group things that have similar properties and separate them into different group if thing has different properties.