# Towards AI-Generated Essay Classification Using Numerical Text Representation
## 3 Natural Language Processing  
Natural language processing (NLP) is a rapidly evolving field with numerous applications and a promising future. Recent breakthroughs, including advances in voice assistants, real-time language translation, and AI-driven customer support, are revolutionizing the way we interact with technology today. NLP, a vast interdisciplinary field at the intersection of linguistics and computer science [11], continues to evolve. Its essence lies in accurately understanding language structures and formal rules while applying this knowledge in technological contexts. 'Natural language' refers to a way of communication that is not strictly governed by formalized constraints [12]. Early approaches to NLP focused on automating language analysis in terms of its linguistic structure and developing fundamental technologies like machine translation and speech synthesizers. Over time, significant advances in existing tools have expanded their applications. Innovative technologies such as dialogue systems, tools to explore social networks for various social insights, and sentiment analysis solutions that identify user emotions toward products and services have emerged [13]. Natural language can be analyzed at various levels corresponding to the degrees of detail with which it can be represented. From the perspective of natural language processing, the key levels include morphology, syntax, semantics, and pragmatics. Morphology is a branch of linguistics that focuses on the description of words and their inflections. It includes word formation and inflection. The morphological level is associated with the morpheme, defined as the smallest communicative unit in the morphological plane of the language. In other words, it is the smallest indivisible part of a word that carries meaning. The morpheme forms the basis for the construction of more complex linguistic units [14]. 'Syntax' refers to the grammatical structure and organization of words in sentences. The term derives from the Greek word _syntaxis_, which means arrangement or ordering. These concepts are often used interchangeably. Nowadays, syntax refers to the subsystem of language that focuses on utterances, which are units in the syntactic plane. 'Syntax' is also defined as the field of linguistics that describes the structure of sentences and their classification, the relationships between words that make up a sentence, and the ways of expressing individual parts of sentences and their functions [14]. This enables the analysis of sentence structure and identification of the role of individual words in the context of a sentence. Semantics deals with the study of the meaning of words, phrases, and sentences. At this level, the meaning of words in specific sentences and the relationships between them are analyzed. Currently, semantics focuses on the relationships between the meaning of words and their form, as well as the relationships between the basic definition of a word and its actual meaning in a specific sentence [14]. This involves analyzing how the structure and context of a word or phrase can affect its meaning. For instance, the same word may carry different meanings depending on its grammatical form or how it is used in a sentence, requiring careful interpretation to understand its specific meaning in context. An additional challenge in natural language processing is the existence of homonyms (words that sound the same or are spelled the same but have different meanings), polysemes (words with multiple meanings), and synonyms (different words with the same or similar meanings). Semantic research also encompasses these areas [14]. 'Pragmatics' refers to the analysis of language meaning in the context of linguistic communication. Pragmatics includes studies on the ways language is used in interactions, the purpose and effectiveness of utterances, the interpretation of the speaker's intentions, as well as non-linguistic factors, such as social or contextual aspects [14].