2022
DOI: 10.1007/978-3-031-15791-2_15
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HanKA: Enriched Knowledge Used by an Adaptive Cooking Assistant

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Cited by 1 publication
(3 citation statements)
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“…The results show that the system behaves robustly in low-confidence scenarios and that, in most of the cases, it succeeds both in identifying the correctness of a recipe but also establishing a satisfactory way of providing the necessary advice to the user. In contrast to other systems, we lay on the side of real-time feedback, which is missing [13] or partially missing [14] from recent approaches, but also on the side of easier deployment, since our approach does not depend on specialized hardware [11,14]. However, since all of these approaches concentrate on different aspects of recipe preparation, we conclude that future efforts should consider the outcomes from all of them.…”
Section: Discussionmentioning
confidence: 99%
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“…The results show that the system behaves robustly in low-confidence scenarios and that, in most of the cases, it succeeds both in identifying the correctness of a recipe but also establishing a satisfactory way of providing the necessary advice to the user. In contrast to other systems, we lay on the side of real-time feedback, which is missing [13] or partially missing [14] from recent approaches, but also on the side of easier deployment, since our approach does not depend on specialized hardware [11,14]. However, since all of these approaches concentrate on different aspects of recipe preparation, we conclude that future efforts should consider the outcomes from all of them.…”
Section: Discussionmentioning
confidence: 99%
“…Furthermore, it does not include real-time feedback on the existing state of the recipe. Finally, the learning part of HanKA [14] is the planning of individual tasks of the recipe. Planning is very useful, especially for an inexperienced user; however, the entire system depends on existing devices, which can be discovered and controlled externally.…”
Section: Discussionmentioning
confidence: 99%
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