Computational linguistics is a field at the intersection of computer science and linguistics, where specialised algorithms and software are used to analyse natural human language. The goal is to enable computers to understand, interpret, and generate text in a way that is both meaningful and efficient. This field is at the heart of many technologies used in everyday life such as virtual assistants, translation software, and speech recognition systems.
Text Analytics, also known as Text Mining, is a subdivision of computational linguistics that involves extracting high-quality information from text. This process generally involves structuring the input text, deriving patterns within the structured data, and finally evaluating and interpreting the output. Text analytics has numerous applications including sentiment analysis, where the sentiment of the writer is determined, and topic modelling, where the main themes of the text are determined.
Despite the considerable progress in computational linguistics and text analytics, several issues still exist. One particular challenge is understanding the context of words and sentences, as the same word may convey different meanings in different contexts. Despite these challenges, the potential of these fields is becoming increasingly recognised, with ongoing research and development paving the way for more sophisticated natural language processing and understanding. These technologies are becoming integral parts of numerous industries including healthcare, financial services, customer service, and marketing.
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