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Similarity Search and Applications [electronic resource] : 16th International Conference, SISAP 2023, A Coruña, Spain, October 9-11, 2023, Proceedings / edited by Oscar Pedreira, Vladimir Estivill-Castro.

Contributor(s): Material type: TextTextLanguage: English Series: Publication details: Cham : Springer Nature Switzerland : Imprint: Springer, 2023.Edition: 1st ed. 2023Description: XXI, 310 p. 103 illus., 92 illus. in color. online resourceISBN:
  • 9783031469947
Subject(s): DDC classification:
  • 025.04 23
Online resources:
Contents:
Keynotes -- From Intrinsic Dimensionality to Chaos and Control: Towards a Unified Theoretical View -- The Rise of HNSW: Understanding Key Factors Driving the Adoption -- Towards a Universal Similarity Function: the Information Contrast Model and its Application as Evaluation Metric in Artificial Intelligence Tasks -- Research Track -- Finding HSP Neighbors via an Exact, Hierarchical Approach -- Approximate Similarity Search for Time Series Data Enhanced by Section Min-Hash -- Mutual nearest neighbor graph for data analysis: Application to metric space clustering -- An Alternating Optimization Scheme for Binary Sketches for Cosine Similarity Search -- Unbiased Similarity Estimators using Samples -- Retrieve-and-Rank End-to-End Summarization of Biomedical Studies -- Fine-grained Categorization of Mobile Applications through Semantic Similarity Techniques for Apps Classification -- Runs of Side-SharingTandems in Rectangular Arrays -- Turbo Scan: Fast Sequential Nearest Neighbor Search in High Dimensions -- Class Representatives Selection in Non-Metric Spaces for Nearest Prototype Classification -- The Dataset-similarity-based Approach to Select Datasets for Evaluation in Similarity Retrieval -- Suitability of Nearest Neighbour Indexes for Multimedia Relevance Feedback -- Accelerating k-Means Clustering with Cover Trees -- Is Quantized ANN Search Cursed? Case Study of Quantifying Search and Index Quality -- Minwise-Independent Permutations with Insertion and Deletion of Features -- SDOclust: Clustering with Sparse Data Observers -- Solving k-Closest Pairs in High-Dimensional Data using Locality- Sensitive Hashing -- Vec2Doc: Transforming Dense Vectors into Sparse Representations for Efficient Information Retrieval -- Similarity Search with Multiple-Object Queries -- Diversity Similarity Join for Big Data -- Indexing Challenge -- Overview of the SISAP 2023 Indexing Challenge -- Enhancing Approximate Nearest Neighbor Search: Binary-Indexed LSH-Tries, Trie Rebuilding, And Batch Extraction -- General and Practical Tuning Method for Off-the-Shelf Graph-Based Index: SISAP Indexing Challenge Report by Team UTokyo -- SISAP 2023 Indexing Challenge - Learned Metric Index -- Computational Enhancements of HNSW Targeted to Very Large Datasets -- CRANBERRY: Memory-Effective Search in 100M High-Dimensional CLIP Vectors.
Summary: This book constitutes the refereed proceedings of the 16th International Conference on Similarity Search and Applications, SISAP 2023, held in A Coruña, Spain, during October 9-11, 2023. The 16 full papers and 4 short papers included in this book were carefully reviewed and selected from 33 submissions. They were organized in topical sections as follows: similarity queries, similarity measures, indexing and retrieval, data management, feature extraction, intrinsic dimensionality, efficient algorithms, similarity in machine learning and data mining.
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Item type Current library Call number Materials specified Status Date due Barcode Item holds
E-Books E-Books National Library of India Online Resource 025.04 (Browse shelf(Opens below)) Available EBK000046832ENG
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Keynotes -- From Intrinsic Dimensionality to Chaos and Control: Towards a Unified Theoretical View -- The Rise of HNSW: Understanding Key Factors Driving the Adoption -- Towards a Universal Similarity Function: the Information Contrast Model and its Application as Evaluation Metric in Artificial Intelligence Tasks -- Research Track -- Finding HSP Neighbors via an Exact, Hierarchical Approach -- Approximate Similarity Search for Time Series Data Enhanced by Section Min-Hash -- Mutual nearest neighbor graph for data analysis: Application to metric space clustering -- An Alternating Optimization Scheme for Binary Sketches for Cosine Similarity Search -- Unbiased Similarity Estimators using Samples -- Retrieve-and-Rank End-to-End Summarization of Biomedical Studies -- Fine-grained Categorization of Mobile Applications through Semantic Similarity Techniques for Apps Classification -- Runs of Side-SharingTandems in Rectangular Arrays -- Turbo Scan: Fast Sequential Nearest Neighbor Search in High Dimensions -- Class Representatives Selection in Non-Metric Spaces for Nearest Prototype Classification -- The Dataset-similarity-based Approach to Select Datasets for Evaluation in Similarity Retrieval -- Suitability of Nearest Neighbour Indexes for Multimedia Relevance Feedback -- Accelerating k-Means Clustering with Cover Trees -- Is Quantized ANN Search Cursed? Case Study of Quantifying Search and Index Quality -- Minwise-Independent Permutations with Insertion and Deletion of Features -- SDOclust: Clustering with Sparse Data Observers -- Solving k-Closest Pairs in High-Dimensional Data using Locality- Sensitive Hashing -- Vec2Doc: Transforming Dense Vectors into Sparse Representations for Efficient Information Retrieval -- Similarity Search with Multiple-Object Queries -- Diversity Similarity Join for Big Data -- Indexing Challenge -- Overview of the SISAP 2023 Indexing Challenge -- Enhancing Approximate Nearest Neighbor Search: Binary-Indexed LSH-Tries, Trie Rebuilding, And Batch Extraction -- General and Practical Tuning Method for Off-the-Shelf Graph-Based Index: SISAP Indexing Challenge Report by Team UTokyo -- SISAP 2023 Indexing Challenge - Learned Metric Index -- Computational Enhancements of HNSW Targeted to Very Large Datasets -- CRANBERRY: Memory-Effective Search in 100M High-Dimensional CLIP Vectors.

This book constitutes the refereed proceedings of the 16th International Conference on Similarity Search and Applications, SISAP 2023, held in A Coruña, Spain, during October 9-11, 2023. The 16 full papers and 4 short papers included in this book were carefully reviewed and selected from 33 submissions. They were organized in topical sections as follows: similarity queries, similarity measures, indexing and retrieval, data management, feature extraction, intrinsic dimensionality, efficient algorithms, similarity in machine learning and data mining.

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