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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IBISML | 2022-01-18 13:00 |
Online | Online | Local Explanation of Graph Neural Network through Predictive Graph Mining Hinata Asahi, Masayuki Karasuyama (NIT)  IBISML2021-23 |
Graph Neural Networks (GNNs) have attracted wide attention in the data science community. However, predictions of GNNs a... [more] | IBISML2021-23 pp.37-44 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2021-06-28 15:20 |
Online | Online | Predictive Graph Mining using Graphs with Interval Attributes Hinata Asahi, Masayuki Karasuyama (NIT) NC2021-6 IBISML2021-6 |
Graphs have been widely used to represent structured data such as molecular data and traffic networks. In this paper, we... [more] | NC2021-6 IBISML2021-6 pp.39-46 |
| TL | 2018-10-28 13:00 |
Hokkaido | National Institute of Technology, Hakodate College | An investigation of identifier naming strongly linked to specific pattern of program structure Yoshiki Mashima (O.E.C.U.), Sachio Hirokawa (Kyushu Univ.), Kazuhiro Takeuchi (O.E.C.U.) TL2018-40 |
Identifiers in programming language such as variable names, class names, and method names are generally given in natural... [more] | TL2018-40 pp.7-12 |
| ICSS, IPSJ-SPT | 2018-03-07 13:25 |
Hokkaido | Okinawa Hokubu Koyou Nouryoku Kaihatsu Sougou Center | Combining Local and Global Graph-based Features for Stealth Scan Detection on LAN Hiroki Nagayama, Bo HU, Kazunori Kamiya, Masaki Tanikawa (NTT) ICSS2017-52 |
In recent years, the increase of unknown malware is remarkable and it is difficult to prevent malware infiltration by 10... [more] | ICSS2017-52 pp.7-12 |
| ICSS, IPSJ-SPT | 2017-03-14 11:20 |
Nagasaki | University of Nagasaki | Graph based Detection of Advanced Persistent Threat on LAN Hiroki Nagayama, Bo Hu, Takaaki Koyama, Jun Miyoshi (NTT) ICSS2016-65 |
Recently the countermeasures against continuously increasing Advanced Persistent Threats(APT) are urgently necessary. I... [more] |
ICSS2016-65 pp.153-158 |
| NS | 2016-10-21 11:10 |
Hyogo | Himeji Nishi-Harima Area Jibasan Center | Network Topology Components Analysis using Fast Graph Mining Shohei Kamamura, Aki Fukuda, Hiroshi Yamamoto, Hiroki Date, Rie Hayashi, Yoshihiko Uematsu (NTT) NS2016-99 |
We propose a network topology components analysis using fast graph mining. In a backbone network, the network should be ... [more] | NS2016-99 pp.57-62 |
| LOIS | 2016-03-03 13:40 |
Okinawa | Central Community Center, Miyakojima-City | Proposal and Performance Evaluation of Multiple Label Propagation Algorithm for Linked Open Data Generation Toshitaka Maki, Toshihiko Wakahara, Akihiro Yamaguchi (FIT), Yu Ichifuji, Noboru Sonehara (NII) LOIS2015-72 |
In recent years, Linked Open Data (LOD) has been attracting attention in the world. It has been increasing year after ye... [more] | LOIS2015-72 pp.51-56 |
| ICM, LOIS | 2016-01-22 09:55 |
Fukuoka | Fukuoka Institute of Technology | The Construction Method of the Municipality CMS for Linked Open Data Generation Toshitaka Maki, Toshihiko Wakahara, Akihiro Yamaguchi (FIT), Shinichiro Kimoto (Shingu Town Hospitality Association), Akinori Takagi (Shingu Town Office), Yu Ichifuji, Noboru Sonehara (NII) ICM2015-35 LOIS2015-57 |
In this study, we make a Municipality CMS for Linked Open Data (LOD) generation. We realize an information exchange and ... [more] | ICM2015-35 LOIS2015-57 pp.53-58 |
| IBISML | 2015-11-26 15:00 |
Ibaraki | Epochal Tsukuba | [Poster Presentation]
Frequent Subgraph Mining with Wildcards Fumiya Okazaki, Ichigaku Takigawa (Hokkaido Univ.) IBISML2015-56 |
Similar subgraphs that differ in only a few labels are often found in frequent subgraph mining. Therefore frequent su... [more] |
IBISML2015-56 pp.25-32 |
| NLC | 2012-08-31 10:00 |
Kanagawa | Fuji Xerox | A study on extraction of related terms and their visualization from trouble incident reports Osamu Segawa (CEPCO), Kazuhiko Murakami, Munehiro Furusato (Chuden CTI) NLC2012-17 |
We have developed a analysis method for trouble incident reports on our intra-system using text mining technique. These ... [more] | NLC2012-17 pp.41-44 |
| COMP | 2011-10-21 10:35 |
Miyagi | Tohoku Univ. | Fast Algorithm for Finding a Graph Node with High Closeness Centrality Koji Tabata, Atsuyoshi Nakamura, Mineichi Kudo (Hokkaido Univ.) COMP2011-29 |
The Closeness Centrality is one of centrality measures of a node in a graph. It is calculated as the reciprocal of the ... [more] |
COMP2011-29 pp.7-14 |
| IBISML | 2010-06-14 11:20 |
Tokyo | Takeda Hall, Univ. Tokyo | [Invited Talk]
Relational Data Mining on Causal Relations Between Variables Takashi Washio (Osaka Univ.) IBISML2010-3 |
Under development of sensing techniques to ease simultaneous measurements of many variables and features on objects, the... [more] | IBISML2010-3 p.5 |
| PRMU | 2009-02-20 10:00 |
Tokyo | Univ. of Tokyo (IIS) | Study on Spatial Relation-based Mining for CAD Data Hiroaki Kizu, Junko Yamamoto, Takashi Takeda, Keiji Gyohten, Naomichi Sueda (Oita Univ.) PRMU2008-223 |
In this research, we propose CAD data mining technique to obtain semantic elements without prior knowledge about plans b... [more] | PRMU2008-223 pp.93-97 |
| PRMU | 2008-12-18 09:30 |
Kumamoto | Kumamoto Univ. | Video Image Analysis Exploiting Frequent Graph Mining Tomokazu Tsuji, Hisashi Koga, Takanori Yokoyama, Toshinori Watanabe (UEC) PRMU2008-150 |
Frequent graph mining is a technique to extract graph patterns which appear frequently in large set of graphs as useful ... [more] | PRMU2008-150 pp.19-24 |
| ET | 2008-03-08 14:30 |
Tokushima | Tokushima Univ. | New Feature Extraction Scheme from Learning Log Data Using Graph Viewing based on Subgraph Analysis Takahisa Wada, Hiroyuki Oono, Hiroshige Inazumi (Aoyama Gakuin Univ.) ET2007-92 |
By the development of the information system, recording the log of the learning situation and the examination result has... [more] | ET2007-92 pp.47-52 |
| AI | 2007-05-31 15:50 |
Tokyo | Kikai-Shinko-Kaikan Bldg. | An Analysis of Sequential Data with Hierarchical Structure of Time Frame Using Frequent Subtree Mining Ryohei Fukuda, Hiroyuki Oono, Hiroshige Inazumi (Aoyama Gakuin Univ.) AI2007-9 |
Finding hierarchical relations from categorical time series data can be an effective way for feature extraction. To do... [more] |
AI2007-9 pp.45-50 |
| AI | 2007-05-31 16:15 |
Tokyo | Kikai-Shinko-Kaikan Bldg. | New Structure Similarity and Graph Clustering in Matching Any Graph Characterized by Subgraph Distributions Takahisa Wada, Hiroyuki Oono, Hiroshige Inazumi (Aoyama Gakuin Univ.) AI2007-10 |
As a diversification and increases of a complex structure data, the development of a useful DB system and a new data min... [more] | AI2007-10 pp.51-56 |
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