Automatic text processing
Text processing is the automated process that analyses and sorts unstructured text data to obtain valuable insights. By using natural language processing (NLP) and machine learning, sub-branches of artificial intelligence, text processing implements can automatically understand human language and take out value from text data.
We communicate not in numbers but in words. This unstructured data is filled with insights and points of view about different topics, products, and services. Still, companies must first structure and sort textual data to entrance this valuable information.
Statistical Methods.
A word frequency determines the most frequently used words in a specific piece of text.
A collocation helps recognize words that commonly appear together.
A concordance decodes the ambiguity of human language via analyzing how particular words are used in different contexts.
TF-IDF gauges how significant a word is to a document but is offset by the number of documents that hold the word.
Text Classification.
Topic Analysis is a technique for interpreting and categorizing significant text collections following particular topics or themes.
Sentiment Analysis automatically detects the emotional undertones of customer reviews, survey responses, social media posts, etc.
Intent Detection automatically reveals the text's intent, goal, or purpose.
Language Classification models classify text based on language.
Text Extraction.
Keyword Extraction automatically determines and highlights the text's most relevant words or expressions.
Entity Extraction automatically gets names of people, companies, brands, etc. [MonkeyLearn].
An Automatic Text Processing system can identify any tool capable of processing text documents and performing actions or decisions. The main problems inherent in significant amounts of textual data are their structuring and labeling. A structured organization of them certainly helps the searcher search for the data and eases the retrieval of the target documents [Rigutini, p. 2].
Text processing in computing is the automated mechanization of the formation or modification of the electronic text. Computer commands are typically included in text processing helping in the formation of new content or making changes to content, looking for, replacing, formatting, or generating a refined report of the content.
Text processing is concentrated on textual characters at the highest computing level. Moreover, text processing is concerned with conveying information automatically. Unlike an algorithm, text processing can be defined as successively administered macros simpler, with filtering techniques and looking into pattern-action expressions [Technopedia].
Leonardo Rigutini. (2010). Automatic Text Processing: Machine Learning Techniques. Moldova, Chisinau: LAP Lambert Academic Publishing.
Text Processing. Technopedia. Retrieved from: https://www.techopedia.com/definition/22541/text-processing.
Text Processing: What Is It? MonkeyLearn. Retrieved from: https://monkeylearn.com/blog/text-processing/.