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Data · collection · 2016

Statistical Analysis of Text Summarization Evaluation

Listed in DataCite

This dissertation applies statistical methods to the evaluation of automatic summarization using data from the Text Analysis Conferences in 2008-2011.

Description

Several aspects of the evaluation framework itself are studied, including the statistical testing used to determine significant differences, the assessors, and the design of the experiment. In addition, a family of evaluation metrics is developed to predict the score an automatically generated summary would receive from a human judge and its results are demonstrated at the Text Analysis Conference.

Finally, variations on the evaluation framework are studied and their relative merits considered. An over-arching theme of this dissertation is the application of standard statistical methods to data that does not conform to the usual testing assumptions.

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Catalogue records · 2

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Text 75%
Provenance · 1 source records, 8 field assertions
SourceKeyLast seenRaw
DataCite10.13016/m2bz2512 d agoJSON v1
FieldAssertionExtractorEvidence
concepts[field].fos:languages-and-literaturesource · DataCiteconnector:datacite@1.0.0
concepts[field].fos:mathematicssource · DataCiteconnector:datacite@1.0.0
concepts[field].local:field:computer-science-aimapping · DataCitevocabulary-mapper@1.0.0keywords['Computer science']
concepts[field].local:field:mathematics-statisticsmapping · DataCitevocabulary-mapper@1.0.0keywords['Statistics']
concepts[modality].local:modality:textenrichment · DataCitekeyword-concept-rules@1.0.0title+description (75%)
descriptionsource · DataCiteconnector:datacite@1.0.0/data/attributes/descriptions
publication_datesource · DataCiteconnector:datacite@1.0.0/data/attributes/dates
titlesource · DataCiteconnector:datacite@1.0.0/data/attributes/titles/0/title