Skip to Content

Overview of content related to 'text mining'

Syndicate content

This page provides an overview of 1 article related to 'text mining'. Note that filters may be applied to display a sub-set of articles in this category (see FAQs on filtering for usage tips). Select this link to remove all filters.

 'Inspecting article' image: copyright, used under license from shutterstock.com
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). (Excerpt from Wikipedia article: Text mining)

Key statistics

Metadata related to 'text mining' (as derived from all content tagged with this term):

  • Number of articles referring to 'text mining': 21 (1.2% of published articles)
  • Total references to 'text mining' across all Ariadne articles: 138
  • Average number of references to 'text mining' per Ariadne article: 6.57
  • Earliest Ariadne article referring to 'text mining': 2003-07
  • Trending factor of 'text mining': 0 (see FAQs on monitoring of trends)

See our 'text mining' overview for more data and comparisons with other tags. For visualisations of metadata related to timelines, bands of recency, top authors, and and overall distribution of authors using this term, see our 'text mining' usage charts. Usage chart icon

Top authors

Ariadne contributors most frequently referring to 'text mining':

  1. sophia ananiadou (see articles on this topic by this author)
  2. john keane (see articles on this topic by this author)
  3. john mcnaught (see articles on this topic by this author)
  4. paul watry (see articles on this topic by this author)
  5. julia chruszcz (see articles on this topic by this author)

Note: Links to all articles by authors listed above set filters to display articles by each author in the overview below. Select this link to remove all filters.

Title Article summary Date

Beyond the PDF

Jodi Schneider reports on a three-day workshop about the future of scientific communication, held in San Diego CA, USA, in January 2011.

January 2011, issue66, event report

CSVXML
Syndicate content


by Dr. Radut