Similarity Search and Applications 16th International Conference, SISAP 2023, A Coruña, Spain, October 9-11, 2023, Proceedings
by
 
Pedreira, Oscar. editor.

Title
Similarity Search and Applications 16th International Conference, SISAP 2023, A Coruña, Spain, October 9-11, 2023, Proceedings

Author
Pedreira, Oscar. editor.

ISBN
9783031469947

Edition
1st ed. 2023.

Physical Description
XXI, 310 p. 103 illus., 92 illus. in color. online resource.

Series
Lecture Notes in Computer Science, 14289

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.

Added Author
Pedreira, Oscar.
 
Estivill-Castro, Vladimir.

Added Corporate Author
SpringerLink (Online service)

Electronic Access
https://doi.org/10.1007/978-3-031-46994-7


LibraryMaterial TypeItem BarcodeShelf Number[[missing key: search.ChildField.HOLDING]]Status
Online LibraryE-Book521264-1001XX(521264.1)Elektronik Kütüphane