Titlebook: Similarity Search and Applications; 15th International C Tomáš Skopal,Fabrizio Falchi,Marco Patella Conference proceedings 2022 The Editor(

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0302-9743 short and 2 doctoral symposium papers were carefully reviewed and selected from 34 submissions. They were organized in topical sections as follows: Applications; Foundations; Indexing and Clustering; Learning; Doctoral Symposium..978-3-031-17848-1978-3-031-17849-8Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Numerical Data Imputation: Choose kNN over Deep Learningng data problems. The present study compares state-of-the-art DL Generative Adversarial Network (GAN) models with the well-established kNN algorithm (1951) for numerical data imputation. Using real-world and generated datasets in various missing data scenarios, we show that the good old kNN algorith

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COSINER: COntext SImilarity , for Named Entity Recognitiony generate labeled data and improve performance of existing methods. However, based on manipulations of the input text, current techniques may generate too many noisy and mislabeled samples. In this paper we propose ., a method for NER data augmentation based on context similarity, i.e. we replace e

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An Application of Learned Multi-modal Product Similarity to E-Commercee electronic market places. The specific requirements for this similarity search application are (i) the similar products should be competitive products with respect to a given query product, (ii) related and just generally similar products should be treated as not similar products. Thus, the simila

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Stable Anchors for Matching Unlabelled Point Cloudsling method ensuring a consistent selection of points across realizations of the same point cloud. In this work, we present a heuristic to extract a stable anchor from . point clouds when the points have no weights and are indistinguishable. This problem arises when we need to query an extensive col

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Visual Exploration of Human Motion Datae of important open challenges is the presentation of high-dimensional spatio-temporal motion data to end users in a way that is easy to understand and allows fast browsing and exploration of the motion datasets. For many applications such as computer-assisted rehabilitation or motion learning, it i

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