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- W2103450368 abstract "There have been multiple techniques to discover action-rules, but the problem of triggering those rules was left exclusively to domain knowledge and domain experts. When meta-actions are applied on objects to trigger a specific rule, they might as well trigger transitions outside of the target action rule scope. Those additional transitions are called side effects, which could be positive or negative. Negative side effects could be devastating in some domains such as healthcare. In this paper, we strive to reduce those negative side effects by extracting personalized action rules. We proposed three object-grouping schemes with regards to same negative side effects to extract personalized action rules for each object group. We also studied the tinnitus handicap inventory data to apply and compare the three grouping schemes." @default.
- W2103450368 created "2016-06-24" @default.
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- W2103450368 date "2013-01-01" @default.
- W2103450368 modified "2023-10-02" @default.
- W2103450368 title "Personalized Action Rules for Side Effects Object Grouping" @default.
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- W2103450368 doi "https://doi.org/10.4236/ijis.2013.31a004" @default.
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