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What is Text Mining? What are the application areas? What are the challenges? What are the tools?. Prelude. Amount of information is growing exponentially Majority of Information is stored in text documents : journals , web pages , emails, reports, memos, social networks...
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What are the challenges?
What are the tools?
genuinely new information
The discovery by computer of
by automatically extracting information from a usually large amount of different
Deals with structured numeric data
Typically in a data warehouse
“The objective of Text Mining is to exploit information contained in textual documents in various ways, including …discovery of patterns and trends in data, associations among entities, predictive rules, etc.”
“Another way to view text data mining is as a process of exploratory data analysis that leads to heretofore unknown information, or to answers for questions for which the answer is not currently known.”
Is this easy?
TM exploits techniques / methodologiesfromdata mining, machine learning, information retrieval, corpus-based computational linguistics
serve as the incoming 92serve as the incubator 99serve as the independent 794serve as the index 223serve as the indication 72serve as the indicator 120serve as the indicators 45serve as the indispensable 111serve as the indispensible 40serve as the individual 234serve as the industrial 52serve as the industry 607serve as the info 42serve as the informal 102serve as the information 838serve as the informational 41serve as the infrastructure 500serve as the initial 5331serve as the initiating 125serve as the initiation 63serve as the initiator 81serve as the injector 56serve as the inlet 41serve as the inner 87serve as the input 1323serve as the inputs 189serve as the insertion 49serve as the insourced 67serve as the inspection 43serve as the inspector 66serve as the inspiration 1390serve as the installation 136serve as the institute 187Example: Google n-grams
N-gram here concerns words, in other contexts it is used for characters!