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Introduction to text mining

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Lars Juhl Jensen
Lars Juhl Jensen

This document introduces text mining and discusses how it can be used to find relevant papers based on a user query, recognize entities in texts, extract facts using information extraction, and provide information on molecular networks and side effects by analyzing large amounts of text. It acknowledges several researchers who have contributed to this area of work.

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Introduction to text mining Lars Juhl Jensen >10 km
exponential growth
 
~45 seconds per paper
text mining
information retrieval
find the relevant papers
user-specified query
“ yeast AND cell cycle”
 
entity recognition
identify the concepts
comprehensive lexicon
orthographic variation
“ black list”
Reflect
augmented browsing
Pafilis, O’Donoghue, Jensen et al., Nature Biotechnology , 2009
used by publishers
 
information extraction
formalize the facts
co-mentioning
NLP Natural Language Processing
[object Object],[object Object],[object Object],[object Object]
molecular networks
 
information on side effects
Campillos & Kuhn et al., Science , 2008
Acknowledgments ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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Introduction to text mining