Result for "Data Mining",80

NTT Communication Science Laboratories Open House 2013 Efficient graph mining techniques for big data - Fast algorithms for large-scale graphs -

mining techniques for big data - Fast algorithms for large-scale graphs - Abstract Recent advances in

https://www.rd.ntt/cs/event/openhouse/2013/exhibition/bigdata4/index_en.html

NTT Communication Science Laboratories Open House 2017

Exhibition Program 6 Fast mining of relationships of large-scale data An efficient algorithm for L1-graph

https://www.rd.ntt/cs/event/openhouse/2017/exhibition/6/index_en.html

Language Technologies in a Multilingual World

) ----------------------------- Manual encoding of linguistic knowledge into rules Data-Driven Machine Translation (2000—now

https://www.rd.ntt/cs/event/openhouse/2011/talk/research1/openhouse-kevinalbert.pdf

poster_en_6.pdf

, NTT SIC Email：fujiwara.yasuhiro(at)lab.ntt.co.jp Fast mining of relationships of large-scale data - An

https://www.rd.ntt/cs/event/openhouse/2017/exhibition/6/poster_en_6.pdf

poster_en3.pdf

Related works Contact 3 Efficient graph mining techniques for big data Abstract----- Recent

https://www.rd.ntt/cs/event/openhouse/2013/exhibition/bigdata4/poster_en3.pdf

NTT Communication Science Laboratories Open House 2013 Network anomaly detection using big data analysis - Analyzing network failure/cyber attacks and their root causes -

NTT Communication Science Laboratories Open House 2013 Network anomaly detection using big data

https://www.rd.ntt/cs/event/openhouse/2013/exhibition/bigdata5/index_en.html

Atsutoshi Kumagai | NTT R&D Website

Paper Award Papers See More Research Activity. Keywords AI, Machine Learning, Data Mining, Cyber

https://www.rd.ntt/e/organization/researcher/special/s_056.html

Behavioral technology modeling | NTT R&D Website

International Conference on Knowledge Discovery & Data Mining (KDD 2021), pp.1276-1286, 2021. Yuya Hikima

https://www.rd.ntt/e/hil/category/behavior_modeling/

NTT Communication Science Laboratories Open House 2013 Understanding stream data from essential elements - Feature selection for high-dimensional time series data -

- Abstract In this research, we develop a pattern mining technique from high-dimensional time series data

https://www.rd.ntt/cs/event/openhouse/2013/exhibition/bigdata2/index_en.html

Technical fields

-choice behavior modeling of customers, complex system dynamics, social science, data mining Quality

https://www.rd.ntt/e/ns/qos/outline/

NTT Communication Science Laboratories Open House 2015 Program

:30 - 16:10 "When", "where", "what", and "how"? - Spatio-temporal multidimensional data analysis for

https://www.rd.ntt/cs/event/openhouse/2015/program_en.html

Katsumi Takahashi | NTT Social Informatics Laboratories | NTT R&D Website

interested in security problems related to big data/IoT, specifically with privacy concerns. He has developed

https://www.rd.ntt/e/sil/overview/evangelist/katsumi_takahashi.html

H1-H4

Knowledge Discovery and Data Mining (KDD), pp. 363-371, 2008. [4] T. Iwata, A. Shah, Z. Ghahramani

https://www.rd.ntt/cs/event/openhouse/2017/talk/research1/talk_iwata.pdf

NTT Communication Science Laboratories Open House 2014 Smarter and instant analysis for huge amounts of video - Jubatus, a scalable big data real-time analysis framework -

amounts of video - Jubatus, a scalable big data real-time analysis framework - 日本語 English Home Greeting

https://www.rd.ntt/cs/event/openhouse/2014/exhibition/4/index_en.html

ICA2003 Home

, especially in communication, speech, biomedical signal processing, image processing, data mining, finance

https://www.rd.ntt/cs/team_project/icl/signal/ica2003/home.html

NTT Communication Science Laboratories Open House 2019

Factorization for Spatio-Temporal Predictions,” in Proc. of 2017 IEEE International Conference on Data Mining

https://www.rd.ntt/cs/event/openhouse/2019/exhibition6/index_en.html

NTT Communication Science Laboratories Open House 2015

Presentations & Exhibits Schedule Access Download Contact Home / Program / Exhibits Big Data Science Efficient

https://www.rd.ntt/cs/event/openhouse/2015/exhibition/5/index_en.html

poster_en.pdf

clustering, regression, recommendation, classification, and graph mining. We can immediately analyze big data

https://www.rd.ntt/cs/event/openhouse/2014/exhibition/4/poster_en.pdf

Learning and Intelligent Systems Research Group | NTT Communication Science Laboratories | NTT R&D Website

statistical learning theory, data mining, data stream analysis, sensor networks, and more. Group Leader

https://www.rd.ntt/e/cs/team_project/icl/ls/

poster_en_1.pdf

area (ambient noise, motion) - air pollution hot spots (CO, PM2.5…) Data mining server Sensorized

https://www.rd.ntt/cs/event/openhouse/2017/exhibition/1/poster_en_1.pdf

poster_en2.pdf

Graph Mining : Centroids of graphs finding, Shortest path calculation Outlier Detection : Abnormal data

https://www.rd.ntt/cs/event/openhouse/2013/exhibition/bigdata3/poster_en2.pdf

スライド 1

2017 IEEE International Conference on Data Mining (ICDM), 2017. [2] 竹内孝, 鹿島久嗣, 上田修功, “自己回帰テンソル分解による時空間

https://www.rd.ntt/cs/event/openhouse/2019/download/06_a_en.pdf

知能創発環境研究グループ｜NTTコミュニケーション科学基礎研究所｜NTT R&D Website

on Data Mining (SDM), May 2025. Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai, Yuuki Yamanaka

https://www.rd.ntt/cs/team_project/icl/ls/

行動モデリング | NTT R&D Website

& Data Mining (KDD 2022), pp.1306-1316, 2022. Yuya Hikima, Yasunori Akagi, Marumo Naoki, and Hideaki Kim

https://www.rd.ntt/hil/category/behavior_modeling/

PowerPoint Presentation

design and verification)  2000’s: Large-scale combinatorial data processing (Data mining, Knowledge

https://www.rd.ntt/_assets/pdf/sic/event/2017/70/02-minato.pdf

Traffic/network design/management – Publications

unstructured data in telecom services. In DMDM 2008: IEEE International Workshop on Data Mining for Design and

https://www.rd.ntt/e/ns/qos/research/03/presentation.html

NTT Communication Science Laboratories Open House 2015

Presentations & Exhibits Schedule Access Download Contact Home / Program / Exhibits Big Data Science ESKORT

https://www.rd.ntt/cs/event/openhouse/2015/exhibition/9/index_en.html

poster_en.pdf

～Efficient Structure Mining for Large-scale Graph～ [1] Y.Fujiwara,G.Irie, “Efficient Label Propagation”, In

https://www.rd.ntt/cs/event/openhouse/2015/exhibition/5/poster_en.pdf

Latent differentiation inference | NTT Communication Science Laboratories | NTT R&D Website

structure inference is one of the most important topics in machine learning and data mining, especially in

https://www.rd.ntt/e/cs/team_project/media/biomedical_informatics/research_biomedical_informatics10.html

panel-sakurai_hmm.pdf

Knowledge Discovery and Data Mining (KDD), pp. 247-255, Las Vegas, Nevada, August 2008 (Best Paper Awards

https://www.rd.ntt/cs/event/openhouse/2010/theme/b3/panel-sakurai_hmm.pdf

ニュース｜上田特別研究室｜NTTコミュニケーション科学基礎研究所｜NTT R&D Website

」が採録されました。 2016/09 ICDM2016 (IEEE International Conference on Data Mining)に論文「A Semi-supervised AUC

https://www.rd.ntt/cs/team_project/uebetsu/news/

特徴的な構造を抽出するデータマイニング技術

data for deeper data mining データのキモ、見つけます ～特徴的な構造を抽出するデータマイニング技術～ 近年のビッグデータ解析を語るう えで、統計的なデータマイニング 手法の存在

https://www.rd.ntt/cs/event/openhouse/2012/panel/panel_5.pdf

高橋 克巳｜NTT社会情報研究所｜NTT R&D Website

エンティスト。主席研究員。NTTセキュリティマスター。博士（情報理工学） 著書 Efficient Secure Three-Party Sorting with Applications to Data

https://www.rd.ntt/sil/overview/evangelist/katsumi_takahashi.html

News | Ueda Research Laboratory｜NTT Communication Science Laboratories | NTT R&D Website

Models,” was accepted by ICDM2016 (IEEE International Conference on Data Mining). 08/2016 Two of our

https://www.rd.ntt/e/cs/team_project/uebetsu/news/

2012ポスター_english

of your data, isn't it? -Extracting hidden structure of data for deeper data mining- ・Rats can better

https://www.rd.ntt/cs/event/openhouse/2012/oh2012_poster_en.pdf

NTT Communication Science Laboratories Open House 2013 Program

data - Streaming analysis with distributed online machine learning - Efficient graph mining techniques

https://www.rd.ntt/cs/event/openhouse/2013/program_en.html

Statistical Machine Learning | NTT Communication Science Laboratories | NTT R&D Website

mining technology and prediction and inference technology capable of analyzing the multitude of data in

https://www.rd.ntt/e/cs/team_project/icl/ls/research_innovative02.html

スライド 1

Conference on Data Mining (ICDM), 2017. [2] 竹内孝, 鹿島久嗣, 上田修功, “自己回帰テンソル分解による時空間データ予測,” 2018年度人工知能学会全国大会（第32回

https://www.rd.ntt/cs/event/openhouse/2019/download/06_a.pdf

poster.pdf

Conference on Knowledge Discovery and Data Mining (PAKDD), 2016. [2] A. Y. Xue, J. Qi, X. Xie, R. Zhang, J

https://www.rd.ntt/cs/event/openhouse/2016/exhibition/5/poster.pdf

NTT Communication Science Laboratories Open House 2019

Conference on Knowledge Discovery and Data Mining, pp. 1055-1063, 2011. Poster Please click the icon to open

https://www.rd.ntt/cs/event/openhouse/2019/exhibition7/index_en.html

poster_en4.pdf

Related works Contact 4 Network anomaly detection using big data analysis Abstract----- Network

https://www.rd.ntt/cs/event/openhouse/2013/exhibition/bigdata5/poster_en4.pdf

NTT コミュニケーション科学基礎研究所 オープンハウス2019

2017 IEEE International Conference on Data Mining (ICDM), 2017. [2] 竹内孝, 鹿島久嗣, 上田修功, “自己回帰テンソル分解による時空間

https://www.rd.ntt/cs/event/openhouse/2019/exhibition6/

NTT コミュニケーション科学基礎研究所 オープンハウス2019

neighborhood graphs,” in Proc. The 17th ACM SIGKDD International Conference on Knowledge Discovery and Data

https://www.rd.ntt/cs/event/openhouse/2019/exhibition7/

NTT コミュニケーション科学基礎研究所 オープンハウス2013 この子にぴったりな絵本を探す ～幼児単語に重みを置いたグラフベースの類似絵本検索～

Discovery and Data Mining (KDD), pp. 1055-1063, 2011. 展示担当者 平 博順 協創情報研究部 藤田 早苗 協創情報研究部 田中 貴秋 協創情報研究部 小林 哲生

https://www.rd.ntt/cs/event/openhouse/2013/exhibition/media9/

NTT Communication Science Laboratories Open House 2013 Finding picture books suitable for a child - Graph-based similar picture book search with weighted child words -

International Conference on Knowledge Discovery and Data Mining (KDD), pp. 1055-1063, 2011. Presentor Taira

https://www.rd.ntt/cs/event/openhouse/2013/exhibition/media9/index_en.html

NTT Communication Science Laboratories Open House 2017 Program

learning for time-series data Preventing gradient explosions in gated recurrent units Fast mining of

https://www.rd.ntt/cs/event/openhouse/2017/program_en.html

NTT コミュニケーション科学基礎研究所 オープンハウス2013 大規模なグラフデータをあっという間に分析 ～グラフデータを対象とした高速なマイニングアルゴリズム～

with Accuracy Assurance,” in Proc. the 18th ACM SIGKDD Conference on Knowledge Discovery and Data

https://www.rd.ntt/cs/event/openhouse/2013/exhibition/bigdata4/

スライド 1

Conference on Knowledge Discovery and Data Mining, pp. 1055-1063, 2011. The Snow Queen ✔ ✔ phonetic histogram

https://www.rd.ntt/cs/event/openhouse/2019/download/07_a_en.pdf

poster3.pdf

and Data Mining (KDD), 2012. [2] H. Shiokawa, Y. Fujiwara, M. Onizuka, “Fast Algorithm for Modularity

https://www.rd.ntt/cs/event/openhouse/2013/exhibition/bigdata4/poster3.pdf

poster_en21.pdf

SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp. 1055-1063, 2011. Graph

https://www.rd.ntt/cs/event/openhouse/2013/exhibition/media9/poster_en21.pdf