Murata Laboratory is doing research on artificial intelligence, especially Web mining and link mining.


open laboratory: We will open our laboratory from 15:00 to 17:00 on May 6 (Sat), 2017 at Ookayama West-8E building. Please visit the second briefing of the entrance exam (in Japanese) for more information. If you want to know more about master's entrance exam, please see the schedule of briefing (in Japanese) (2017.4.5).

admission: Admission information for International Graduate Program (C) (IGP(C)) is available. If you are interested in our laboratory and want to apply for IGP(C) program, please read this page carefully, and send the following documents to Murata by email as soon as possible: (i) your CV, (ii) your grade transcript(s), (iii) research proposal, (iv) list of publications, and (v) your thesis for graduating master/undergraduate course (if it is not written in English, please send any English technical papers/documents written by you). The deadline of applying IGP(C) is May 9, 2017.(2017.4.5)

admission: If you are a student of (or graduated from) the Partner Schools in asia, you can apply for JICA innovative Asia program. If you are interested our laboratory, please read this page carefully, and send all application documents to Murata by email as soon as possible. The deadline of application is April 20, 2017 May 2, 2017 because we have to finish Skype interviews before the deadline of application (May 2, 2017). (2017.4.12)

call for postdocs: Our laboratory takes part in RWBC-OIL(AIST-Tokyo Tech Real World Big-Data Computation Open Innovation Laboratory).
RWBC-OIL is a joint laboratory of Tokyo Tech and AIST for the analysis of real-world big data started from Feb. 2017 (news from Tokyo Tech (in Japanese), news from AIST (in Japanese)).
RWBC-OIL hires researchers of machine learning / deep learning / graph mining / high performance computing. Please read call for postdocs (in Japanese) for more information. If you are interested in, please contact Murata. (2017.4.6)

Mr. Shun Nukui (title: "Constrained community detection based on semi-supervised non-negative matrix factorization on TensorFlow") received 2016 JSAI Annual Conference Student Incentive Award. (2017.3.1)

Murata was invited to MARAMI 2016 as an invited speaker, but the talk was canceled. (2016.10.14)

Murata gave a talk ("Mining and learning on heterogeneous networks") as an invited speaker at WIMS 2016 (slides). (2016.6.15)

Dr. Xin Liu and Mr. Weichu Liu's paper (title: "Community Detection in Multi-Partite Multi-Relational Networks Based on Information Compression") was accepted by New Generation Computing. (2016.3.7)

Mr. Phiradet Bangcharoensap's paper (title: "Transductive Classification on Heterogeneous Information Networks with Edge Betweenness-based Normalization") was accepted by WSDM 2016 conference (acceptance rate: 18.2%). (2015.10.14)

Mr. Phiradet Bangcharoensap's paper (title: "Two step graph-based semi-supervised learning for online auction fraud detection") was accepted by ECML-PKDD 2015 conference (acceptance rate: 28.6%). (2015.6.3)

Mr. Keisuke Nakata presented his work at CompleNet 2015(the 6th Workshop on Complex Networks). His photo is here. (2015.3.25)

Mr. Keisuke Nakata (title: "Speeding-up of Constrained Community Detection and Development of its Interactive Environment") received JSAI Annual Conference Award. 19 papers were selected out of 584 papers. (2014.7.22)

Dr. Xin Liu and Mr. Weichu Liu's paper (A Framework for Community Detection in Heterogeneous Multi-Relational Networks) was accepted by Advances in Complex Systems.(2014.7.9)

Dr. Xin Liu's paper (Detecting network communities beyond assortativity-related attributes) was accepted by Physical Review E.(2014.6.19)

Mr. Ikematsu's programs for detecting communities from n-partite networks are available online.
Reference:"Improvement of a Tripartite Modularity and Its Optimization Method"(written in Japanese)
(Transactions of the Japanese Society for Artificial Intelligence, Vol.29, No.2, pp.245-258, 2014)(2014.2.20)


Another Web site of Murata laboratory

Department of Computer Science, School of Computing
Tokyo Institute of Technology