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Terminology mining in social media
RISE, Swedish ICT, SICS. Attityd.
RISE, Swedish ICT, SICS. Attityd.ORCID iD: 0000-0003-4042-4919
Number of Authors: 2
2009 (English)Conference paper (Refereed)
Abstract [en]

The highly variable and dynamic word usage in social media presents serious challenges for both research and those commercial applications that are geared towards blogs or other user-generated non-editorial texts. This paper discusses and exempli´Čües a terminology mining approach for dealing with the productive character of the textual environment in social media. We explore the challenges of practically acquiring new terminology, and of modeling similarity and relatedness of terms from observing realistic amounts of data. We also discuss semantic evolution and density, and investigate novel measures for characterizing the preconditions for terminology mining.

Place, publisher, year, edition, pages
2009, 1. , 10 p.
Keyword [en]
Word Space, Distributional Semantics, Random Indexing, Terminology Mining, Social Media, Language Technology, Linguistics
National Category
Computer and Information Science
URN: urn:nbn:se:ri:diva-23546OAI: diva2:1042622
The 18th ACM Conference on Information and Knowledge Management (CIKM 2009), 2-5 November 2009, Hong Kong
Available from: 2016-10-31 Created: 2016-10-31 Last updated: 2017-01-02

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Karlgren, Jussi
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