Toshiyuki Amagasa

发表

Efficient Missing Value Imputation by Maximum Distance Likelihood

Akiyoshi Matono, Savong Bou, Toshiyuki Amagasa, 2023, 2023 IEEE International Conference on Big Data (BigData).

Augmented Lineage: Traceability of Data Analysis Including Complex UDFs

Hiroyuki Kitagawa, Toshiyuki Amagasa, Akiyoshi Matono, 2021, International Conference on Database and Expert Systems Applications.

Augmented lineage: traceability of data analysis including complex UDF processing

T. Amagasa, H. Kitagawa, Akiyoshi Matono, 2022, The VLDB Journal.

DBPowder: A Flexible Object-Relational Mapping Framework Based on a Conceptual Model

Hiroyuki Kitagawa, Toshiyuki Amagasa, Tadashi Murakami, 2013, 2013 IEEE 37th Annual Computer Software and Applications Conference.

Searching XML Documents by Keywords in Structured P2P Networks

Hiroyuki Kitagawa, Toshiyuki Amagasa, Xiaochen Li, 2008, 2008 19th International Workshop on Database and Expert Systems Applications.

Constructing a Web Service System for Large-Scale Meteorological Grid Data

Hiroyuki Kitagawa, Toshiyuki Amagasa, Tatsuya Komano, 2007, Third IEEE International Conference on e-Science and Grid Computing (e-Science 2007).

Implementation of a High-Speed and High-Precision XML Information Retrieval System on Relational Databases

Toshiyuki Amagasa, Masatoshi Yoshikawa, Kenji Hatano, 2005, INEX.

Predicting the decision making chemicals used for bacterial growth

T. Amagasa, Bei-Wen Ying, Kazuha Ashino, 2019, Scientific Reports.

Online User Location Inference Exploiting Spatiotemporal Correlations in Social Streams

Hiroyuki Kitagawa, Yuto Yamaguchi, Toshiyuki Amagasa, 2014, CIKM.

Landmark-based user location inference in social media

Hiroyuki Kitagawa, Yuto Yamaguchi, Toshiyuki Amagasa, 2013, COSN '13.

SILVERRUSH X: Machine Learning-aided Selection of 9318 LAEs at z = 2.2, 3.3, 4.9, 5.7, 6.6, and 7.0 from the HSC SSP and CHORUS Survey Data

T. Nagao, T. Amagasa, K. Shimasaku, 2021, The Astrophysical Journal.

Autonomic active learning strategy using cluster-based ensemble classifier for concept drifts in imbalanced data stream

K. M. Azharul Hasan, T. Amagasa, Bohnishikhan Halder, 2023, Expert Syst. Appl..

Missing information in imbalanced data stream: fuzzy adaptive imputation approach

Toshiyuki Amagasa, Nor Ashidi Mat Isa, Rahat Hossain Faisal, 2021, Applied Intelligence.

An Indexing Scheme for RDF and RDF Schema based on Suffix Arrays

Toshiyuki Amagasa, Masatoshi Yoshikawa, Shunsuke Uemura, 2003, SWDB.

XRel: a path-based approach to storage and retrieval of XML documents using relational databases

Toshiyuki Amagasa, Masatoshi Yoshikawa, Shunsuke Uemura, 2001, ACM Trans. Internet Techn..

GPU-Accelerated Graph Clustering via Parallel Label Propagation

Hiroyuki Kitagawa, Toshiyuki Amagasa, Yusuke Kozawa, 2017, CIKM.

PrIvacy Risks And Countermeasures In Publishing And Mining Social Network Data

Ling Liu, Chiemi Watanabe, Toshiyuki Amagasa, 2011, 7th International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom).

AI-powered Posture Training: Application of Machine Learning in Sitting Posture Recognition Using the LifeChair Smart Cushion

Toshiyuki Amagasa, Katia Bourahmoune, T. Amagasa, 2019, IJCAI.

RDF packages: a scheme for efficient reasoning and querying over large-scale RDF data

Hiroyuki Kitagawa, Toshiyuki Amagasa, Shohei Ohsawa, 2010, Int. J. Web Inf. Syst..

A Path-based Relational RDF Database

Toshiyuki Amagasa, Masatoshi Yoshikawa, Shunsuke Uemura, 2005, ADC.

Energy-Efficient XML Stream Processing through Element-Skipping Parsing

Hiroyuki Kitagawa, Toshiyuki Amagasa, Mana Seino, 2013, 2013 24th International Workshop on Database and Expert Systems Applications.

A Graph-Based Blocking Approach for Entity Matching Using Contrastively Learned Embeddings

John Bosco Mugeni, Toshiyuki Amagasa, 2022, ACM SIGAPP Applied Computing Review.

Retrieving Arbitrary XML Fragments from Structured Peer-to-Peer Networks

Hiroyuki Kitagawa, Toshiyuki Amagasa, Chunhui Wu, 2007, APWeb/WAIM.

Extracting XML data from the web

Hiroyuki Kitagawa, Toshiyuki Amagasa, Ngo Sy Viet Phu, 2010, iiWAS.

BPF: a novel cluster boundary points detection method for static and streaming data

H. Kitagawa, V. Khalique, Toshiyuki Amagasa, 2023, Knowledge and Information Systems.

Frequent-Pattern Based Facet Extraction from Graph Data

Hiroyuki Kitagawa, Toshiyuki Amagasa, Takahiro Komamizu, 2014, 2014 17th International Conference on Network-Based Information Systems.

Buffer-based adaptive fuzzy classifier

T. Amagasa, S. Belhaouari, M. Ahmed, 2022, Applied intelligence (Boston).

Scaling Fine-grained Modularity Clustering for Massive Graphs pdf

Hiroyuki Kitagawa, Toshiyuki Amagasa, Hiroaki Shiokawa, 2019, IJCAI.

A Scheme for Efficient Question Answering with Low Dimension Reconstructed Embeddings

Toshiyuki Amagasa, Happy Buzaaba, Happy Buzaaba, 2021, iiWAS.

A graph-based blocking approach for entity matching using pre-trained contextual embedding models

T. Amagasa, John Bosco Mugeni, Toshiyuki Amagasa, 2022, SAC.

Intelligent Posture Training: Machine-Learning-Powered Human Sitting Posture Recognition Based on a Pressure-Sensing IoT Cushion

T. Amagasa, Karlos Ishac, Katia Bourahmoune, 2022, Sensors.

TURank: Twitter User Ranking Based on User-Tweet Graph Analysis

Hiroyuki Kitagawa, Yuto Yamaguchi, Toshiyuki Amagasa, 2010, WISE.

Label-bag based Graph Anonymization via Edge Addition

Gautam Srivastava, H. Kitagawa, Chongjie Li, 2014, C3S2E.