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

Dr.Naonori Ueda | NTT R&D Website

「Fundamentals of Computational Life Science」，December 16, 2020. "Relational data mining based on nonparametric

https://www.rd.ntt/e/organization/researcher/fellow/f_003.html

スライド 1

and Data Mining, pp. 1055-1063, 2011. いろいろな観点で絵本を探せます。 観点1: あらすじ 観点2: お気に入りの絵本と内容が似ている 観点3: 画風が似

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

poster21.pdf

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

https://www.rd.ntt/cs/event/openhouse/2013/exhibition/media9/poster21.pdf

NAKANO, Yuusuke

International Conference on Data Mining Workshops (ICDMW), 2021, pp. 278-287, doi: 10.1109/ICDMW53433.2021.00042

https://www.rd.ntt/e/ns/qos/person/y_nakano/

Keynote Speech 3｜NTT R&D FORUM 2023 — IOWN ACCELERATION Report

, but to make the LLM smarter by improving the quality and quantity of training data added to it. As a

https://www.rd.ntt/e/forum/2023/keynote_3.html

NTT R&D FORUM — Road to IOWN 2021｜Exhibits｜ NTT R&D Website

era/age Optical transport with security against quantum computer S02 Utilizing of data to accelerate

https://www.rd.ntt/e/forum/2021/exhibits.html

Keynote Speech 1｜NTT R&D FORUM 2023 — IOWN ACCELERATION Report

of energy consumption that has become a global issue. As you know, the dramatic increase in data

https://www.rd.ntt/e/forum/2023/keynote_1.html

Interview: Distinguished Researcher Kyosuke Nishida｜NTT R&D Website

the field of GPS log data mining and behavior modeling. I think a major advantage we have is that team

https://www.rd.ntt/e/ai/0002.html

Technology for Forecasting the Global Environment and Human Society | NTT R&D Website

the center of Typhoon Hinnamnor in August 2022. For future work, we will analyze the experimental data

https://www.rd.ntt/e/research/JN202212_20365.html

0074.pdf

been applied in various prob- lems, such as blind source separation, noise reduction, and data mining

https://www.rd.ntt/cs/team_project/icl/signal/ica2003/cdrom/data/0074.pdf

交通ダイナミクスやAIモデルの分散学習技術 | NTT R&D Website

Nonhomogeneous Data", ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2020), 2020

https://www.rd.ntt/iown_tech/post_35.html

上田 修功 | NTT R&D Website

International Workshop on Smart Cities(IWSC): People, Technology and Data, 2016. Reviewer, International

https://www.rd.ntt/organization/researcher/fellow/f_003.html

Lebreton_MMSP2018.pdf

: studies that use data mining to understand the relationship between quality factors and user engagement

https://www.rd.ntt/e/ns/qos/research/01/pdf/Lebreton_MMSP2018.pdf

Lebreton_MMSP2018.pdf

: studies that use data mining to understand the relationship between quality factors and user engagement

https://www.rd.ntt/e/ns/qos/person/yamagishi/pdf/Lebreton_MMSP2018.pdf

Recognition Research Group | NTT Communication Science Laboratories | NTT R&D Website

. the 26th Conference on Knowledge Discovery and Data Mining (ACM SIGKDD), 2020, pp. 187-197. O. Krishna

https://www.rd.ntt/e/cs/team_project/media/recognition/

2019_booklet_english.pdf

Spatio-Temporal Predictions,” in Proc. of 2017 IEEE International Conference on Data Mining (ICDM), 2017

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

Forefront Initiatives of NTT Space Environment and Energy Laboratories | NTT R&D Website

-demand/supply control technology is beginning to attract attention as a new concept called "power to data

https://www.rd.ntt/e/research/JN202401_24530.html

ｽﾗｲﾄﾞ ﾀｲﾄﾙなし

分析 技術文書分析 購買関係分析 商品推薦 技術トレンド分析 共著者分析 キーワード分析 SNS分析 画像・センサー分析 Linked Open Data分析 研究開発 高速化・分析アルゴリズム・可視化

https://www.rd.ntt/_assets/pdf/sic/event/2017/70/07-iida.pdf

メディア認識研究グループ｜NTTコミュニケーション科学基礎研究所｜NTT R&D Website

Knowledge Discovery and Data Mining (ACM SIGKDD), 2020, pp. 187-197. O. Krishna, G. Irie, X. Wu, T

https://www.rd.ntt/cs/team_project/media/recognition/

oh2017_booklet.pdf

and Data Mining (KDD), pp. 664-672, 2010. [2] T. Iwata, J. Lloyd, Z. Ghahramani, “Unsupervised many-to

https://www.rd.ntt/cs/event/openhouse/2017/download/oh2017_booklet.pdf

西田 京介 | NTT R&D Website

ChatGPT", The 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, May 2023. 西田京介, 壹岐太一

https://www.rd.ntt/organization/researcher/superior/s_033.html

PowerPoint プレゼンテーション

Data, and the merger of DOCOMO, NTT Communications, and NTT COMWARE. In Chapter 2, we will organize and

https://www.rd.ntt/e/sil/overview/NTTannual2023_e_web.pdf

ica03wiener.dvi

algorithm for deter- mining this optimal system, inspired from a similar method used in blind source

https://www.rd.ntt/cs/team_project/icl/signal/ica2003/cdrom/data/0132.pdf

oh08_pamphlet.pdf

リスト> 山崎 徳之（やまざきのりゆき） ■講演題目 「Derive implicit data from explicit data on social graph」 株式会社ゼロ

https://www.rd.ntt/cs/event/openhouse/2008/doc/oh08_pamphlet.pdf

Microsoft PowerPoint - 2018.03.09.ビッグデータ分析技術ワークショップ_公開用.pptx

ク R&D部部長 東京大学 客員研究員 興味領域 – Social Media Mining – Computational Social Science – Social Network

https://www.rd.ntt/_assets/pdf/sic/event/2018/1/06_sakaki.pdf

oh1013_booklet.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/download/oh1013_booklet.pdf

ntt冊子2012.indd

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 手法の存在は無視

https://www.rd.ntt/cs/event/openhouse/2012/oh2012_booklet.pdf

2019_booklet.pdf

Proc. The 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining , pp. 1055

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

OH2010.pdf

for Hidden Markov Models”, ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

https://www.rd.ntt/cs/event/openhouse/2010/OH2010.pdf

oh2016_booklet.pdf

Proc. the 20th Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2016. [2] A. Y

https://www.rd.ntt/cs/event/openhouse/2016/download/oh2016_booklet.pdf