(2019) The 7 Basic Functions of Text Analytics Источник: https://www.lexalytics.com/lexablog/text-analytics-functions-explained
QUOTE | Text analytics and natural language processing are often portrayed as ultra-complex computer science functions that can only be understood by trained data scientists. But the truth is that the core concepts are pretty easy to understand (though to be fair, the the actual technology is quite complicated). In this quick, high-level overview we’re going to review the basic functions of text analytics, and explore how each contributes to deeper natural language processing features.
Quick background: text analytics refers to a discipline of computer science that combines machine learning and natural language processing (NLP) to draw meaning from unstructured text documents. |
QUOTE | Much like a student writing an essay on Hamlet, a text analytics engine must break down sentences and phrases before it can actually analyze anything. Tearing apart unstructured text documents into their component parts the first step in pretty much every NLP feature, including named entity recognition, theme extraction, and sentiment analysis. |
QUOTE | There are 7 basic steps involved in preparing an unstructured text document for deeper analysis:
Language Identification Tokenization Sentence Breaking Part of Speech Tagging Chunking Syntax Parsing Sentence Chaining |
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