In this paper, we propose the locality-sensitive hashing (LSH) based graph partitioning algorithm whose time/space complexity is O(n), n is the number of vertices in graph. For all kinds of hyperscale graphs, it works at the speed of random partitioning method approximately. Compared with ...
Right now, we're using xxhash in #641 for our prefix cache-aware router. We might consider switching to a consistent hash + LSH-based approach, which could reduce accuracy a bit but would simplify scaling. Here are some related discussions: vllm-project/production-stack#59 (comment). Use ...
A visual graph editor based on G6 and React. Contribute to lsh-sihong/GGEditor development by creating an account on GitHub.
云计算环境下基于倒排lsh的高维近似图象检索方法 Cloud computing environment inverted lsh high dimensional approximation based Image Retrieval本发明公开了一种云计算环境下基于倒排LSH的高维近似图象检索方法,属于基于大数据与移动应用领域. The present invention discloses a large part based on data and mobile ...
Lightweight and personalised e-commerce recommendation based on collaborative filtering and LSH 来自 掌桥科研 喜欢 0 阅读量: 49 作者: D Li,JA Esquivel 摘要: Nowadays, e-commerce has become one of the most popular shopping ways for worldwide customers especially after the outbreak of COVID-...
Reference identifiers for the reference videos are stored in bins of the reference index associated with the identified keys. The bins in the reference index are sub-sampled to limit the number of reference identifiers stored in a given bin....
Reference identifiers for the reference videos are stored in bins of the reference index associated with the identified keys. The bins in the reference index are sub-sampled to limit the number of reference identifiers stored in a given bin.doi:US8069176 B1Sergey IoffeMichele CovellUS...
In view of the above challenges, in this paper, we propose a novel prediction method for the missing traffic flow data caused by abnormal sensors, named A S M V P d i s t r - L S H based on distributed locality-sensitive hashing (LSH) technique. At last, a case study is ...
First, LSH is adopted to determine nearest neighbor set of the target users, where a neighbor matrix for the target user can be generated. The matrix factorization technique is applied in the neighbor matrix to predict the missing ratings. Then the nearest neighbors can be determined based on ...
A locality-sensitive hashing (LSH) technique has recently been employed to achieve the abovementioned privacy-preservation goal. However, traditional LSH-based recommendation approaches often suffer from low accuracy when the service quality data recruited in recommendations vary in a big range. ...