Similarity Search and Applications

13th International Conference, SISAP 2020, Copenhagen, Denmark, September 30 – October 2, 2020, Proceedings

AvShin'ichi Satoh,Lucia Vadicamo

Häftad, Engelska, 2020

Del 12440 i serien Lecture Notes in Computer Science

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Beskrivning

This book constitutes the refereed proceedings of the 13th International Conference on Similarity Search and Applications, SISAP 2020, held in Copenhagen, Denmark, in September/October 2020.

Produktinformation

Utgivningsdatum:2020-10-15
Mått:155 x 235 x 31 mm
Vikt:662 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:414
Förlag:Springer Nature Switzerland AG
ISBN:9783030609351

Utforska kategorier

Systemvetenskap och AI inom Data och IT
Databaser inom Data och IT
Artificiell intelligens inom Data och IT

Innehållsförteckning

Scalable Similarity Search.- Accelerating Metric Filtering by Improving Bounds on Estimated Distances.- Differentially Private Sketches for Jaccard Similarity Estimation.- Pivot Selection for Narrow Sketches by Optimization Algorithms.- mmLSH: A Practical and Efficient Technique for Processing Approximate Nearest Neighbor Queries on Multimedia Data.- Parallelizing Filter-Verification based Exact Set Similarity Joins on Multicores.- Similarity Search with Tensor Core Units.- On the Problem of p1 in Locality-Sensitive Hashing.- Similarity Measures, Search, and Indexing.- Confirmation Sampling for Exact Nearest Neighbor Search.- Optimal Metric Search Is Equivalent to the Minimum Dominating Set Problem.- Metrics and Ambits and Sprawls, Oh My: Another Tutorial on Metric Indexing.- Some branches may bear rotten fruits: Diversity browsing VP-Trees.- Continuous Similarity Search for Evolving Database.- Taking advantage of highly-correlated attributes in similarity queries with missing values.- Similarity Between Points in Metric Measure Spaces.- High-dimensional Data and Intrinsic Dimensionality.- GTT: Guiding the Tensor Train Decomposition.- Noise Adaptive Tensor Train Decomposition for Low-Rank Embedding of Noisy Data.- ABID: Angle Based Intrinsic Dimensionality.- Sampled Angles in High-Dimensional Spaces.- Local Intrinsic Dimensionality III: Density and Similarity.- Analysing Indexability of Intrinsically High-dimensional Data using TriGen.- Reverse k-Nearest Neighbors Centrality Measures and Local Intrinsic Dimension.- Clustering.- BETULA: Numerically Stable CF-Trees for BIRCH Clustering.- Using a Set of Triangle Inequalities to Accelerate K-means Clustering.- Angle-Based Clustering.- Artificial Intelligence and Similarity.- Improving Locality Sensitive Hashing by Efficiently Finding Projected Nearest Neighbors.- SIR: Similar Image Retrieval for Product Search in E-Commerce.- Cross-Resolution deep features based Image Search.- LearningDistance Estimators from Pivoted Embeddings of Metric Objects.- Demo and Position Papers.- Visualizer of Dataset Similarity using Knowledge Graph.- vitrivr-explore: Guided Multimedia Collection Exploration for Ad-hoc Video Search.- Running experiments with confidence and sanity.- Doctoral Symposium.- Temporal Similarity of Trajectories in Graphs.- Relational Visual-Textual Information Retrieval.

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