Markow chain is a probabilistic process used to predict the next step based on the probabilities of the existing related states.
English or any other language as a matter of fact is difficult for a computer to understand, especially when the meaning is ambiguous.
I picked a newspaper article and while reading it I was trying to understand the internal workings of how I am forming meaning in those sentences. Like most of the semantic analytics in theory we don’t really need the whole sentence before we start forming the meaning.
The DIKW Pyramid, also known variously as the “DIKW Hierarchy“, “Wisdom Hierarchy“, the “Knowledge Hierarchy“, the “Information Hierarchy“, and the “Knowledge Pyramid“, refers loosely to a class of models for representing purported structural and/or functional relationships between data, information, knowledge, and wisdom.
When I try to understand a particular sentence, I have a feeling that my mind is automatically trying to break the complex words into simpler sentences and then trying to process the whole meaning.
Understanding thoughts on the basis of Nouns or Verbs is not taking me anywhere to close building a thought machine.
Lets talk about a hypothetical software program to solve a simple problem of taking a natural language question like – “What was the last painting of Leonardo Da vinci?”.