Titlebook: Similarity Search and Applications; 14th International C Nora Reyes,Richard Connor,Jian-Jia Chen Conference proceedings 2021 Springer Natur

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How Many Neighbours for Known-Item Search? engines for one or just a few nearest neighbours to a query does not have to be sufficient to accomplish a challenging search task. In this work, we investigate a task type where users search for one particular multimedia object in a large database. Complexity of the task is empirically demonstrate

Plaque

On Generalizing Permutation-Based Representations for Approximate Searchith large data collections. These methods employ a permutation-based representation of the data, which can be efficiently indexed using data structures such as inverted files. In the literature, the definition of the permutation of a metric object was derived by reordering the distances of the objec

thwart

Data-Driven Learned Metric Index: An Unsupervised Approach data or divide space using hyper-planes. While searching, the mutual distances between objects and the metric properties allow for the pruning of branches with irrelevant data – this is usually implemented by utilizing selected anchor objects called pivots. Recently, we have introduced an alternati

多产鱼

wall-stress

Fierce

废墟

Optimizing Fair Approximate Nearest Neighbor Searches Using Threaded B+-Treesor solving the Approximate Nearest Neighbor (ANN) problem in high-dimensional spaces. Along with creating fair machine learning models, there is also a need for creating data structures that target different types of fairness. In this paper, we propose a fair variant of the ANN problem that targets

genesis

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