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20212026
most citedFast and Exact Outlier Detection in Metric Spaces: A Proximity Graph-based Approach

3 citations · 5 across the 11 of their papers we have counts for

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6 papers · 1 filter

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.DB20213 cited

Fast and Exact Outlier Detection in Metric Spaces: A Proximity Graph-based Approach

Daichi Amagata, Makoto Onizuka, Takahiro Hara

Distance-based outlier detection is widely adopted in many fields, e.g., data mining and machine learning, because it is unsupervised, can be employed in a generic metric space, an…

cs.DB2021

Reverse Maximum Inner Product Search: How to efficiently find users who would like to buy my item?

Daichi Amagata, Takahiro Hara

The MIPS (maximum inner product search), which finds the item with the highest inner product with a given query user, is an essential problem in the recommendation field. It is usu…

cs.DB2021

Distributed Spatial-Keyword kNN Monitoring for Location-aware Pub/Sub

Shohei Tsuruoka, Daichi Amagata, Shunya Nishio +1

Recent applications employ publish/subscribe (Pub/Sub) systems so that publishers can easily receive attentions of customers and subscribers can monitor useful information generate…