Nyelvfeldolgozás

Nyelvfeldolgozás is the Hungarian term for Natural Language Processing (NLP). It is a subfield of artificial intelligence (AI) and computer science that focuses on enabling computers to understand, interpret, and generate human language. This involves developing algorithms and models that can process and analyze large amounts of text and speech data.

The core of nyelvfeldolgozás lies in breaking down language into its constituent parts and understanding the relationships between them. This includes tasks such as tokenization, where text is divided into individual words or sub-word units, and stemming or lemmatization, which reduces words to their root form. Part-of-speech tagging assigns grammatical categories to words, while named entity recognition identifies and classifies entities like people, organizations, and locations.

Nyelvfeldolgozás plays a crucial role in a wide range of applications. Machine translation systems, like Google Translate, use NLP to translate text between different languages. Chatbots and virtual assistants, such as Siri and Alexa, rely on NLP to understand user queries and provide relevant responses. Sentiment analysis, another application, helps determine the emotional tone of text, which is valuable for market research and social media monitoring. Text summarization and question answering systems also fall under the umbrella of NLP, aiming to condense information and extract specific answers from documents. The continuous advancements in deep learning have significantly boosted the capabilities of nyelvfeldolgozás, leading to more accurate and sophisticated language understanding and generation.