Domain-Independent Mining of Abstracts Using Indicator Phrases

• Autores: Ron Daniel
• Localización: D-Lib Magazine, ISSN-e 1082-9873, Vol. 18, Nº. 7-8, 2012
• Idioma: inglés
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• Resumen

  • Abstracts contain a variety of domain-independent indicator phrases such as "These results suggest X" and "X remains unknown". Indicator phrases locate domain-specific key phrases (the Xs) and categorize them into potentially useful types such as research achievements and open problems. We hypothesized that such indicator phrases would allow reliable extraction of domain-specific information, in a variety of disciplines, using techniques with low computational burden. The low burden and domain-independence are major requirements for applications we are targeting. We report on an analysis of indicator phrases in a collection of 10,000 abstracts, and a more detailed analysis of the automated tagging of 100 abstracts from ten different disciplines. We found that a modest number (18) of regular expressions can achieve reasonable performance (F1 ~= 0.7, Precision ~= 0.8) in extracting information about achievements, problems, and applications across the 10 different disciplines.