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- W4205955777 abstract "In this chapter, we automatically build a decision tree (DecT) from textual data relying on discourse analysis. We refer to such tree as supported, as each decision node is supported with a text fragment the respective rule is extracted from. A DecT can be built from multiple documents as well as traditional attribute-value data. We propose a step-by-step procedure for building discourse trees (DTs) from text and then constructing a DecT from multiple DTs. We also evaluate the correctness and completeness of the formed DecTs in the making diagnoses for a series of diseases, given various textual descriptions of symptoms. We conclude the chapter with an extensive survey of expert systems leveraging DecT algorithms." @default.
- W4205955777 created "2022-01-26" @default.
- W4205955777 creator A5071035935 @default.
- W4205955777 date "2022-01-01" @default.
- W4205955777 modified "2023-09-25" @default.
- W4205955777 title "Obtaining supported decision trees from text for health system applications" @default.
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- W4205955777 doi "https://doi.org/10.1016/b978-0-12-824521-7.00013-2" @default.
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