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Sep 16, 2022 · This study proposes a privacy-preserving collaborative filtering recommendation method with clustering and locality-sensitive hashing.
We use a locality-sensitive hashing algorithm to reduce the dimensionality of the user rating data and build an index that could quickly obtain the neighbors of ...
We use a locality‐sensitive hashing algorithm to reduce the dimensionality of the user rating data and build an index that could quickly obtain the neighbors of ...
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What is the locality sensitive hashing technique?
Is locality sensitive hashing clustering?
We use a locality‐sensitive hashing algorithm to reduce the dimensionality of the user rating data and build an index that could quickly obtain the neighbors of ...
The Locality Sensitive Hashing (LSH) technique of scalably finding nearest-neighbors can be adapted to enable discovering similar users while preserving their ...
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Aug 28, 2024 · In this paper, we have proposed a Privacy-preserving Diversified Service Recommendation (PDSR) method. The method leverages LSH mechanism to ...
In this paper, we propose a Locality Sensitive Hashing (LSH) based approach for federated recommender system.
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In this paper, we propose RSUC, a privacy-preserving Recommender System based on User Classification. RSUC incorporates homomorphic encryption for better data ...
Locality sensitive hashing (LSH) is a widely popular technique used in approximate nearest neighbor (ANN) search.
Jul 30, 2023 · LSH is a technique that efficiently approximates similarity search by reducing the dimensionality of data while preserving local distances between points.