Text Mining

Text mining, sometimes alternately referred to as text data mining, roughly equivalent to text analytics, refers to the process of deriving high-quality information from text. High-quality information is typically derived through the devising of patterns and trends through means such as statistical pattern learning. Text mining usually involves the process of structuring the input text (usually parsing, along with the addition of some derived linguistic features and the removal of others, and subsequent insertion into a database), deriving patterns within the structured data, and finally evaluation and interpretation of the output. 'High quality' in text mining usually refers to some combination of relevance, novelty, and interestingness. Typical text mining tasks include text categorization, text clustering, concept/entity extraction, production of granular taxonomies, sentiment analysis, document summarization, and entity relation modeling (i.e., learning relations between named entities).

Text analysis involves information retrieval, lexical analysis to study word frequency distributions, pattern recognition, tagging/annotation, information extraction, data mining techniques including link and association analysis, visualization, and predictive analytics. The overarching goal is, essentially, to turn text into data for analysis, via application of natural language processing (NLP) and analytical methods.

A typical application is to scan a set of documents written in a natural language and either model the document set for predictive classification purposes or populate a database or search index with the information extracted.

Read more about Text MiningText Mining and Text Analytics, History, Text Analysis Processes, Applications, Software and Applications, Implications

Other articles related to "text mining, text, mining":

Text Analytics
... Text mining, also referred to as text data mining, roughly equivalent to text analytics, refers to the process of deriving high-quality information from text ... Text mining usually involves the process of structuring the input text (usually parsing, along with the addition of some derived linguistic features and the removal of others, and ... 'High quality' in text mining usually refers to some combination of relevance, novelty, and interestingness ...
List Of Chatterbots - Processes of NLP - Component Processes
... Automatic document classification (text categorization) – Automatic language identification – Discourse analysis – includes a number of related tasks ... One task is identifying the discourse structure of connected text, i.e ... possible task is recognizing and classifying the speech acts in a chunk of text (e.g ...
List Of Natural Language Processing Toolkits - Processes of NLP - Component Processes - Component Processes of Natural Language Understanding
... Automatic document classification (text categorization) – Automatic language identification – Compound term processing – category of techniques that identify compound terms and match them to ... Corpus processing – Automatic acquisition of lexicon – Text normalization – Text simplification – Deep linguistic processing – Discourse analysis – includes a number of related tasks ... One task is identifying the discourse structure of connected text, i.e ...
Text Analytics - See Also
... matrix factorization, an algorithm used for text mining BioCreative text mining evaluation in biomedical literature Concept Mining Name resolution Stop words Text ... Web mining, a task that may involve text mining (e.g ... then extract the desired information from the text content of these pages considered relevant) ...
Text Mining - Implications
... Until recently, websites most often used text-based searches, which only found documents containing specific user-defined words or phrases ... Now, through use of a semantic web, text mining can find content based on meaning and context (rather than just by a specific word) ... Additionally, text mining software can be used to build large dossiers of information about specific people and events ...

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