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• W2070147364 endingPage "664" @default.
• W2070147364 startingPage "647" @default.
• W2070147364 abstract "Four experiments were conducted to assess two models of topic sentencehood identification: the derived model and the free model. According to the derived model, topic sentences are identified in the context of the paragraph and in terms of how well each sentence in the paragraph captures the paragraph’s theme. In contrast, according to the free model, topic sentences can be identified on the basis of sentential features without reference to other sentences in the paragraph (i.e., without context). The results of the experiments suggest that human raters can identify topic sentences both with and without the context of the other sentences in the paragraph. Another goal of this study was to develop computational measures that approximated each of these models. When computational versions were assessed, the results for the free model were promising; however, the derived model results were poor. These results collectively imply that humans’ identification of topic sentences in context may rely more heavily on sentential features than on the relationships between sentences in a paragraph." @default.
• W2070147364 created "2016-06-24" @default.
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• W2070147364 date "2008-08-01" @default.
• W2070147364 modified "2023-09-25" @default.
• W2070147364 title "Identifying topic sentencehood" @default.
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• W2070147364 doi "https://doi.org/10.3758/brm.40.3.647" @default.
• W2070147364 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/18697660" @default.
• W2070147364 hasPublicationYear "2008" @default.
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