Locality Sensitive Hashing (LSH)
The distortion of locality sensitive hashing
... objects, locality sensitive hashing (LSH) aims to construct a hash function family over the universe of objects such that the probability two objects hash to the same value is their ...
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Query-Adaptative Locality Sensitive Hashing
... hoc approaches have been proposed for vector quantization (see [3] for references), when finding the exact nearest neighbor is not ex- actly necessary, as long as the reconstruction error is limited. More specific ANN ...
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Research on Improved Locality Sensitive Hashing Algorithm
... using locality sensitive hashing algorithm to find data label , in order to compensate its susceptible to noise points, propose locality sensitive hashing algorithm based on ...
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Lattice-based locality sensitive hashing is optimal
... Locality sensitive hashing (LSH) was introduced by Indyk and Motwani (STOC ‘98) to give the first sublinear time algorithm for the c-approximate nearest neighbor (ANN) problem using only polynomial ...
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An Efficient Recommender System Using Locality Sensitive Hashing
... etc. Locality sensitive hashing is one of the state-of-the-art efficient algorithms that approximately preserving similarity but with significant dimension ...
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Bayesian locality sensitive hashing for fast similarity search
... of locality-sensitive hashing [12, 10], where the idea is to find a family of hash functions such that for a random hash function from this family, two objects with high similarity are very likely to ...
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Similarity join size estimation using locality sensitive hashing
... In this paper, we propose sampling based techniques that exploit the Locality Sensitive Hashing (LSH) scheme, which has been successfully applied in similarity searches across many domains. LSH ...
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Text and Content Based Image Retrieval Via Locality Sensitive Hashing
... the hashing schemes applied on the edge histograms and the auto colour correlograms, ...the locality sensitive hashing package that was used in the retrieving ...
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Boosting multi-kernel Locality-Sensitive Hashing for scalable image retrieval
... 6. CONCLUSIONS This paper investigated a framework of Multi-Kernel Locality- Sensitive Hashing by exploring multiple kernels for efficient and scalable content-based image retrieval. We first ...
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Privacy-preserving distributed service recommendation based on locality-sensitive hashing
... However, traditional CF-based service recommendation approaches often assume that the historical user-service quality data is centralized, while neglect the distributed recommendation situation. Generally, distributed ...
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Locality sensitive hashing: a comparison of hash function types and querying mechanisms
... curse of dimensionality (B¨ohm et al., 2001; Beyer et al., 1999). This operation is required by many pattern recognition appli- cations. In image retrieval or object recognition, the numer- ous descriptors of an image ...
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Accelerating Large Scale Centroid-based Clustering with Locality Sensitive Hashing
... Queen’s University Belfast {rmcconville07, x.cao, w.liu, p.miller}@qub.ac.uk Abstract—Most traditional data mining algorithms struggle to cope with the sheer scale of data efficiently. In this paper, we propose a general ...
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Multi-resolution sketches and locality sensitive hashing for fast trajectory processing
... develop Locality sensitive hashing (LSH) for this approximation problem, and it was subsequently improved upon in various works to obtain a query time sublinear in n, and polynomial dependence in d ...
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Faster sieving for shortest lattice vectors using spherical locality-sensitive hashing
... is locality-sensitive hashing (LSH), introduced by Indyk and Motwani ...[21]. Locality-sensitive hash functions are functions h which map n-dimensional vectors w to low-dimensional ...
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Employing Ontology-Alignment and Locality-Sensitive Hashing to Improve Attribute Interoperability in Federated eID Systems
... Exposing attributes to this entity might violate defined privacy rules. To tackle these issues and to allow the aligning and aggregation of attributes in eID federations, new ground has to be broken. In this paper, we, ...
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Instance based Inductive Deep Transfer Learning by Cross Dataset Querying with Locality Sensitive Hashing
... Background Locality Sensitive Hashing (LSH): Locality Sen- sitive Hashing (Gao et ...independent hashing technique as the hash functions are selected at random, which makes LSH ...
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Fast document summarization using locality sensitive hashing and memory access efficient node ranking
... Although we use min-hashing to compress large sets into small signatures while yet preserving the expected similarity of any pair of sentences, there is still another very important issue. Finding the pairs of ...
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An evaluation of multi probe locality sensitive hashing for computing similarities over web scale query logs
... * [email protected] Abstract Many modern applications of AI such as web search, mobile browsing, image processing, and natural language processing rely on finding similar items from a large database of com- plex ...
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A Distributed Locality Sensitive Hashing Based Approach for Cloud Service Recommendation From Multi Source Data
... Abstract—To maximize the economic benefits, a cloud service provider needs to recommend its services to as many users as possible based on the historical user-service quality data. However, when a cloud platform (e.g., ...
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An Online Malicious Spam Email Detection System Using Resource Allocating Network with Locality Sensitive Hashing
... the Locality Sensitive Hashing (LSH) [10]-[14] to quickly select important training data to be ...with Locality Sensitive Hashing (RAN-LSH) as a classifier model in the proposed ...
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