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cs.DB2026

Duration-constrained Interval Joins

Naoya Ehara, Daichi Amagata

Many databases, including temporal, uncertain, spatial, and trajectory databases, use interval data, and interval joins are among the most frequently used operators. Many studies p…

cs.DB2026

Simple and Fast Algorithm for Graph-based Filtered Approximate Nearest Neighbor Search (Full Version)

Reon Uemura, Keito Kido, Daichi Amagata

It has been common to represent many objects as high-dimensional vectors due to the proliferation of machine learning-based embedding techniques. One of the most important function…

cs.DB2025

Random Sampling over Spatial Range Joins

Daichi Amagata

Spatial range joins have many applications, including geographic information systems, location-based social networking services, neuroscience, and visualization. However, joins inc…

cs.DB2025

Approximate Reverse -Ranks Queries in High Dimensions

Daichi Amagata, Kazuyoshi Aoyama, Keito Kido +1

Many objects are represented as high-dimensional vectors nowadays. In this setting, the relevance between two objects (vectors) is usually evaluated by their inner product. Recentl…

cs.DB2025

How to Mine Potentially Popular Items? A Reverse MIPS-based Approach

Daichi Amagata, Kazuyoshi Aoayama, Keito Kido +1

The -MIPS ( Maximum Inner Product Search) problem has been employed in many fields. Recently, its reverse version, the reverse -MIPS problem, has been proposed. Given an i…

cs.DB2024

Independent Range Sampling on Interval Data (Longer Version)

Daichi Amagata

Many applications require efficient management of large sets of intervals because many objects are associated with intervals (e.g., time and price intervals). In such interval mana…