As natural language processing is a comprehensive problem, it is examined in different phases and by combining these phases, natural language processing applications can be developed. Each of the following layers has separate specialties within themselves.
If you want to analyze and understand a written data, these layers are; There is a need for dominant tools in the fields of morphology, syntax and semantics. However, in the case of data audio files, support should be obtained from phonetic and phonology layers in addition to these layers.
Natural Language Processing in Written Content with Artiwise
Artiwise Analytics allows you to use Natural Language Processing techniques, such as root cause analysis, morphological analysis, Turkish character correction, named entity detection, without the need to write code or technical development.
Natural Language Processing sub-discipline aims to mimic the ability of people to speak and especially to understand spoken. One of the greatest talents that make people human is speaking and understanding. There are many words in the community that this is the most important feature that distinguishes man from other beings. For this reason, if we are talking about a humanoid computer, it is the most important feature that people can understand and realize their speeches. At the same time, the differences in people’s use of language, their specificity, etc. Many details make this problem harder to solve.
The most important motivation of this discipline is how people learn a language. Scientists who have been trying to solve this work for years by transferring the rules of languages to computer environment have seen the impossibility of reaching a definite conclusion with these methods and have tried many kinds of artificial intelligence techniques. This problem is not a problem we can say today is fully solved. Languages live and evolve with people. Therefore, as long as people exist, these studies will continue to be done.