Matches in SemOpenAlex for { <https://semopenalex.org/work/W2943382023> ?p ?o ?g. }
Showing items 1 to 55 of
55
with 100 items per page.
- W2943382023 abstract "This paper introduces fact-checking into Machine Learning (ML) explanation by referring training data points as facts to users to boost user trust. We aim to investigate what influence of training data points, and how they affect user trust in order to enhance ML explanation and boost user trust. We tackle this question by allowing users check the training data points that have the higher influence and the lower influence on the prediction. A user study found that the presentation of influences significantly increases the user trust in predictions, but only for training data points with higher influence values under the high model performance condition, where users can justify their actions with more similar facts." @default.
- W2943382023 created "2019-05-09" @default.
- W2943382023 creator A5003763151 @default.
- W2943382023 creator A5031848640 @default.
- W2943382023 creator A5032481596 @default.
- W2943382023 creator A5037660639 @default.
- W2943382023 creator A5047165067 @default.
- W2943382023 creator A5051364953 @default.
- W2943382023 creator A5056429995 @default.
- W2943382023 date "2019-05-02" @default.
- W2943382023 modified "2023-10-07" @default.
- W2943382023 title "Effects of Influence on User Trust in Predictive Decision Making" @default.
- W2943382023 cites W1581658097 @default.
- W2943382023 cites W2103542834 @default.
- W2943382023 cites W2153680437 @default.
- W2943382023 cites W2548571880 @default.
- W2943382023 cites W2763906873 @default.
- W2943382023 cites W4240637756 @default.
- W2943382023 doi "https://doi.org/10.1145/3290607.3312962" @default.
- W2943382023 hasPublicationYear "2019" @default.
- W2943382023 type Work @default.
- W2943382023 sameAs 2943382023 @default.
- W2943382023 citedByCount "10" @default.
- W2943382023 countsByYear W29433820232019 @default.
- W2943382023 countsByYear W29433820232020 @default.
- W2943382023 countsByYear W29433820232021 @default.
- W2943382023 countsByYear W29433820232022 @default.
- W2943382023 countsByYear W29433820232023 @default.
- W2943382023 crossrefType "proceedings-article" @default.
- W2943382023 hasAuthorship W2943382023A5003763151 @default.
- W2943382023 hasAuthorship W2943382023A5031848640 @default.
- W2943382023 hasAuthorship W2943382023A5032481596 @default.
- W2943382023 hasAuthorship W2943382023A5037660639 @default.
- W2943382023 hasAuthorship W2943382023A5047165067 @default.
- W2943382023 hasAuthorship W2943382023A5051364953 @default.
- W2943382023 hasAuthorship W2943382023A5056429995 @default.
- W2943382023 hasConcept C41008148 @default.
- W2943382023 hasConceptScore W2943382023C41008148 @default.
- W2943382023 hasLocation W29433820231 @default.
- W2943382023 hasOpenAccess W2943382023 @default.
- W2943382023 hasPrimaryLocation W29433820231 @default.
- W2943382023 hasRelatedWork W1596801655 @default.
- W2943382023 hasRelatedWork W2049775471 @default.
- W2943382023 hasRelatedWork W2350741829 @default.
- W2943382023 hasRelatedWork W2358668433 @default.
- W2943382023 hasRelatedWork W2376932109 @default.
- W2943382023 hasRelatedWork W2382290278 @default.
- W2943382023 hasRelatedWork W2390279801 @default.
- W2943382023 hasRelatedWork W2748952813 @default.
- W2943382023 hasRelatedWork W2899084033 @default.
- W2943382023 hasRelatedWork W2530322880 @default.
- W2943382023 isParatext "false" @default.
- W2943382023 isRetracted "false" @default.
- W2943382023 magId "2943382023" @default.
- W2943382023 workType "article" @default.