Search Results for author: Yasuo Tabei

Found 6 papers, 4 papers with code

Space-efficient Feature Maps for String Alignment Kernels

no code implementations18 Feb 2018 Yasuo Tabei, Yoshihiro Yamanishi, Rasmus Pagh

We present novel space-efficient feature maps (SFMs) of RFFs for a space reduction from O(dD) of the original FMs to O(d) of SFMs with a theoretical guarantee with respect to concentration bounds.

Statistically Discriminative Sub-trajectory Mining

no code implementations6 May 2019 Vo Nguyen Le Duy, Takuto Sakuma, Taiju Ishiyama, Hiroki Toda, Kazuya Nishi, Masayuki Karasuyama, Yuta Okubo, Masayuki Sunaga, Yasuo Tabei, Ichiro Takeuchi

Given two groups of trajectories, the goal of this problem is to extract moving patterns in the form of sub-trajectories which are more similar to sub-trajectories of one group and less similar to those of the other.

Dynamic Path-Decomposed Tries

2 code implementations14 Jun 2019 Shunsuke Kanda, Dominik Köppl, Yasuo Tabei, Kazuhiro Morita, Masao Fuketa

Recent applications handling massive keyword dictionaries in main memory have a need for a space-efficient implementation.

$b$-Bit Sketch Trie: Scalable Similarity Search on Integer Sketches

1 code implementation18 Oct 2019 Shunsuke Kanda, Yasuo Tabei

In this paper, we present a novel space-efficient trie named $b$-bit sketch trie on integer sketches for scalable similarity searches by leveraging the idea behind succinct data structures (i. e., space-efficient data structures while supporting various data operations in the compressed format) and a favorable property of integer sketches as fixed-length strings.

Succinct Trit-array Trie for Scalable Trajectory Similarity Search

1 code implementation21 May 2020 Shunsuke Kanda, Koh Takeuchi, Keisuke Fujii, Yasuo Tabei

To address this problem, we present the trajectory-indexing succinct trit-array trie (tSTAT), which is a scalable method leveraging LSH for trajectory similarity searches.

Dynamic Similarity Search on Integer Sketches

1 code implementation24 Sep 2020 Shunsuke Kanda, Yasuo Tabei

However, most similarity search methods are designed for binary sketches and inefficient for integer sketches.

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