Similarity Search and Applications
Springer International Publishing (Verlag)
978-3-031-17848-1 (ISBN)
SISAP 2022 is an annual international conference for researchers focusing on similarity search challenges and related theoretical/practical problems, as well as the design of content-based similarity search applications. The 15 full papers presented together with 8 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.
Applications.- Numerical Data Imputation: Choose KNN over Deep Learning.- COSINER: COntext SImilarity data augmentation for Named Entity Recognition.- An Application of Learned Multi-Modal Product Similarity to e-Commerce.- Deep Vision-Language Model for Efficient Multi-modal Similarity Search in Fashion Retrieval.- Stable Anchors for Matching Unlabelled Point Clouds.- Visual Exploration of Human Motion Data.- Foundations.- On Projections to Linear Subspaces.- Concept of Relational Similarity Search.- On the Expected Exclusion Power of Binary Partitions for Metric Search.- Similarity Search with the Distance Density Model.- Generalized Relative Neighborhood Graph (GRNG) for Similarity Search.- A Ptolemaic Partitioning Mechanism.- HubHSP graph: effective data sampling for pivot-based representation strategies.- Indexing and Clustering.- Compacted search tree for graph edit distance computation.- Clustering by Direct Optimization of the Medoid Silhouette.- Automatic Indexing for Similarity Search in ELKI.- Approximate Nearest Neighbor Search on Standard Search Engines.- Evaluation of LID-Aware Graph Embedding Methods for Node Clustering.- Similarity-based Unsupervised Evaluation of Outlier Detection.- Learning.- FastHebb: Scaling Hebbian Training of Deep Neural Networks to ImageNet Level.- Causal Disentanglement with Network Information for Debiased Recommendations.- Causal Disentanglement with Network Information for Debiased Recommendations.- Self-supervised Information Retrieval Trained from Self-generated Sets of Queries and Relevant Documents.- Doctoral Symposium.- Discovering Knowledge Graphs Via Attention-Driven Graph Generation.- Visual Recommendation and Visual Search for Fashion e-commerce.
| Erscheinungsdatum | 30.09.2022 |
|---|---|
| Reihe/Serie | Lecture Notes in Computer Science |
| Zusatzinfo | XI, 305 p. 97 illus., 84 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 492 g |
| Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
| Schlagworte | Applications • Computer Science • conference proceedings • Informatics • Research |
| ISBN-10 | 3-031-17848-3 / 3031178483 |
| ISBN-13 | 978-3-031-17848-1 / 9783031178481 |
| Zustand | Neuware |
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