Matches in SemOpenAlex for { <https://semopenalex.org/work/W4386977144> ?p ?o ?g. }
Showing items 1 to 57 of
57
with 100 items per page.
- W4386977144 abstract "With increasing frequency of high-profile privacy breaches in various online platforms, users are becoming more concerned about their privacy. And recommender system is the core component of online platforms for providing personalized service, consequently, its privacy preservation has attracted great attention. As the gold standard of privacy protection, differential privacy has been widely adopted to preserve privacy in recommender systems. However, existing differentially private recommender systems only consider static and independent interactions, so they cannot apply to sequential recommendation where behaviors are dynamic and dependent. Meanwhile, little attention has been paid on the privacy risk of sensitive user features, most of them only protect user feedbacks. In this work, we propose a novel DIfferentially Private Sequential recommendation framework with a noisy Graph Neural Network approach (denoted as DIPSGNN) to address these limitations. To the best of our knowledge, we are the first to achieve differential privacy in sequential recommendation with dependent interactions. Specifically, in DIPSGNN, we first leverage piecewise mechanism to protect sensitive user features. Then, we innovatively add calibrated noise into aggregation step of graph neural network based on aggregation perturbation mechanism. And this noisy graph neural network can protect sequentially dependent interactions and capture user preferences simultaneously. Extensive experiments demonstrate the superiority of our method over state-of-the-art differentially private recommender systems in terms of better balance between privacy and accuracy." @default.
- W4386977144 created "2023-09-23" @default.
- W4386977144 creator A5046565976 @default.
- W4386977144 creator A5063091745 @default.
- W4386977144 date "2023-09-16" @default.
- W4386977144 modified "2023-10-18" @default.
- W4386977144 title "Towards Differential Privacy in Sequential Recommendation: A Noisy Graph Neural Network Approach" @default.
- W4386977144 doi "https://doi.org/10.48550/arxiv.2309.11515" @default.
- W4386977144 hasPublicationYear "2023" @default.
- W4386977144 type Work @default.
- W4386977144 citedByCount "0" @default.
- W4386977144 crossrefType "posted-content" @default.
- W4386977144 hasAuthorship W4386977144A5046565976 @default.
- W4386977144 hasAuthorship W4386977144A5063091745 @default.
- W4386977144 hasBestOaLocation W43869771441 @default.
- W4386977144 hasConcept C119857082 @default.
- W4386977144 hasConcept C123201435 @default.
- W4386977144 hasConcept C124101348 @default.
- W4386977144 hasConcept C132525143 @default.
- W4386977144 hasConcept C153083717 @default.
- W4386977144 hasConcept C154945302 @default.
- W4386977144 hasConcept C23130292 @default.
- W4386977144 hasConcept C38652104 @default.
- W4386977144 hasConcept C41008148 @default.
- W4386977144 hasConcept C50644808 @default.
- W4386977144 hasConcept C509729295 @default.
- W4386977144 hasConcept C557471498 @default.
- W4386977144 hasConcept C80444323 @default.
- W4386977144 hasConceptScore W4386977144C119857082 @default.
- W4386977144 hasConceptScore W4386977144C123201435 @default.
- W4386977144 hasConceptScore W4386977144C124101348 @default.
- W4386977144 hasConceptScore W4386977144C132525143 @default.
- W4386977144 hasConceptScore W4386977144C153083717 @default.
- W4386977144 hasConceptScore W4386977144C154945302 @default.
- W4386977144 hasConceptScore W4386977144C23130292 @default.
- W4386977144 hasConceptScore W4386977144C38652104 @default.
- W4386977144 hasConceptScore W4386977144C41008148 @default.
- W4386977144 hasConceptScore W4386977144C50644808 @default.
- W4386977144 hasConceptScore W4386977144C509729295 @default.
- W4386977144 hasConceptScore W4386977144C557471498 @default.
- W4386977144 hasConceptScore W4386977144C80444323 @default.
- W4386977144 hasLocation W43869771441 @default.
- W4386977144 hasOpenAccess W4386977144 @default.
- W4386977144 hasPrimaryLocation W43869771441 @default.
- W4386977144 hasRelatedWork W2598406783 @default.
- W4386977144 hasRelatedWork W2899211198 @default.
- W4386977144 hasRelatedWork W2981499034 @default.
- W4386977144 hasRelatedWork W3035493623 @default.
- W4386977144 hasRelatedWork W3092618973 @default.
- W4386977144 hasRelatedWork W3176515490 @default.
- W4386977144 hasRelatedWork W4226426276 @default.
- W4386977144 hasRelatedWork W4304208041 @default.
- W4386977144 hasRelatedWork W4313492014 @default.
- W4386977144 hasRelatedWork W4383469366 @default.
- W4386977144 isParatext "false" @default.
- W4386977144 isRetracted "false" @default.
- W4386977144 workType "article" @default.