UID:
almahu_9948595008102882
Umfang:
XIX, 414 p. 210 illus., 104 illus. in color.
,
online resource.
Ausgabe:
1st ed. 2020.
ISBN:
9783030609368
Serie:
Information Systems and Applications, incl. Internet/Web, and HCI ; 12440
Inhalt:
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. The conference was held virtually due to the COVID-19 pandemic. The 19 full papers presented together with 12 short and 2 doctoral symposium papers were carefully reviewed and selected from 50 submissions. The papers are organized in topical sections named: scalable similarity search; similarity measures, search, and indexing; high-dimensional data and intrinsic dimensionality; clustering; artificial intelligence and similarity; demo and position papers; and doctoral symposium.
Anmerkung:
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 -- Learning Distance 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.
In:
Springer Nature eBook
Weitere Ausg.:
Printed edition: ISBN 9783030609351
Weitere Ausg.:
Printed edition: ISBN 9783030609375
Sprache:
Englisch
DOI:
10.1007/978-3-030-60936-8
URL:
https://doi.org/10.1007/978-3-030-60936-8
