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Database Information Systems

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Research Frontiers in Vector Database Indexing for High-Dimensional Data

Study of approximate nearest neighbor search structures and indexing methods optimized for similarity queries on embeddings and high-dimensional vectors.

Curse of Dimensionality in Learned Index Structures

Adaptive Quantization for Streaming Vector Embeddings

Hierarchical Decomposition of Ultra-High Dimensional Spaces

Temporal Coherence in Evolving Vector Indexes

Hybrid Geometry: Bridging Metric and Semantic Distance

Sketching-Based Approximation for Billion-Scale Vector Search

Cross-Modal Vector Alignment Without Explicit Embeddings

Energy-Aware Indexing in Distributed Vector Databases

Locality-Sensitive Hashing Beyond Random Projections

Cardinality-Aware Partitioning for Skewed Vector Distributions

All Database & Information Systems PhD categories