Shusaku Egami

I am a researcher at Artificial Intelligence Research Center (AIRC), National Institute of Advanced Industrial Science and Technology (AIST), Japan, where I work on knowledge graph and semantic technology. I am also a part-time lecturer at Hosei University, where I teach semantic web (spring) and agent technology (fall). I am also collaborative researcher at The University of Electro-Communications (UEC) (Ohsuga, Tahara, & Sei Lab ).

I did my PhD at UEC, where I was advised by Takahiro Kawamura and Akihiko Ohsuga and funded by the JSPS DC2.

Email / CV / Bio / / / / / / /

Shusaku Egami

English | 日本語

Research

I'm interested in semantic web, ontology, graph representation learning, and open data. Much of my research is about constructing and reasoning knowledge graphs from physical and cyber world (unstructured text, semistructured data, video, virtual space, etc.).

Peer-reviewed Journal Papers

11.
Shusaku Egami, Takahiro Kawamura, Kouji Kozaki, Akihiko Ohsuga
Data Intelligence, Vol.4, No.1, pp.88-111, 2022
DOI: https://doi.org/10.1162/dint_a_00113 (open access)

We extracted urban problem causality from various documents and structured the data as a KG. Then we detected vicious cycles and root problems using SPARQL and SWRL. Furthermore, urban-problem experts evaluated the extracted causal relations.

10. Campus Ontology-Based Correlation Detection Among Heterogeneous Data Sets
Yuto Tsukagoshi, Shusaku Egami, Yuichi Sei, Yasuyuki Tahara, Akihiko Ohsuga
IEEJ Transactions on Electronics, Information and Systems, Vol.141, No.11, pp.1222-1233, 2021 (in Japanese)
DOI: https://doi.org/10.1541/ieejeiss.141.1222

We collected unstructured data from a university campus and integrated it as a knowledge graph based on the proposed ontology.

9. An Ontology-based Approach for Semantic Interoperability in Air Traffic Information Management
Shusaku Egami, Xiaodong Lu, Tadashi Koga, Yasuto Sumiya
Transactions of the Japanese Society for Artificial Intelligence, Vol.36, No.1, pp.WI2-F_1-12, 2021.1 (in Japanese)
project page /
DOI: https://doi.org/10.1527/tjsai.36-1_WI2-F (open access)

We developed a reference ontology that enables common situational awareness of spatiotemporal concepts for semantic interoperability in air traffic information management.

8. Bilingual Textual Similarity in Scientific Documents
Takahiro Kawamura, Shusaku Egami
IEEE Transactions on Engineering Management, Vol.68, No.5, 2021
project page /
DOI: https://doi.org/10.1109/TEM.2019.2946886 (open access)

We proposed a method for creating word and paragraph vectors corresponding to bilingual textual information in the same multidimensional space, aiming to construct a bilingual map of science.

7. Construction of Urban Problem LOD using Crowdsourcing
Shusaku Egami, Takahiro Kawamura, Kouji Kozaki, Akihiko Ohsuga
International Journal of Smart Computing and Artificial Intelligence, Vol.3, No.1, pp.71-86, 2019
DOI: https://doi.org/10.52731/ijscai.v3.i1.321 (open access)

We extracted causal relations using natural language processing and crowdsourcing to construct urban problem Linked Data.

6. Funding map using paragraph embedding based on semantic diversity
Takahiro Kawamura, Katsutaro Watanabe, Naoya Matsumoto, Shusaku Egami, Mari Jibu
Scientometrics, Vol.116, pp.941-958, 2022
project page /
DOI: https://doi.org/10.1007/s11192-018-2783-x (open access)

We proposed a new content-based method of locating research projects in a multi-dimensional space using the word/paragraph embedding techniques.

5. Temporal and Spatial Expansion of Urban LOD for Solving Illegally Parked Bicycles in Tokyo
Shusaku Egami, Takahiro Kawamura, Akihiko Ohsuga
IEICE Transactions on Information and Systems, Vol.E101-D, No.1, pp.116-129, 2018

DOI: https://doi.org/10.1587/transinf.2017SWP0010 (open access)

We complemented temporal and spatial missing data of the Linked Open Data (LOD) of the problem of illegally parked bicycles using bayesian networks and computational fluid dynamics.

4. Designing and Publishing Illegally Parked Bicycle LOD
Shusaku Egami, Takahiro Kawamura, Akihiko Ohsuga
International Journal of Smart Computing and Artificial Intelligence, Vol.1, No.2, pp.77-93, 2017
DOI: https://doi.org/10.52731/ijscai.v1.i2.99 (open access)

We proposed a schema of illegally parked bicycle LOD (IPBLOD) and a methodology of designing LOD schema.

3. Proposal of Eco-Cycle for Solving Illegally Parked Bicycles using Linked Open Data
Shusaku Egami, Takahiro Kawamura, Akihiko Ohsuga
Transactions of the Japanese Society for Artificial Intelligence, Vol.31, No.6, pp.AI30-K_1-12, 2016 (in Japanese)
DOI: https://doi.org/10.1527/tjsai.AI30-K (open access)

We purposed eco-cycle for solving illegally parked bicycles using linked open data.

2. A Solution to Visualize Open Urban Data for Illegally Parked Bicycles
Shusaku Egami, Takahiro Kawamura, Yuichi Sei, Yasuyuki Tahara, Akihiko Ohsuga
Transactions on Large-Scale Data and Knowledge-Centered Systems XXVII, Springer LNCS, Vol.9860, pp.129-141, 2016
DOI: https://doi.org/10.1007/978-3-662-53416-8_8

We built an ecosystem that generates Open Urban Data in Link Data format while complementing missing attribute values.

1. Building of Industrial Parts LOD for BOM Agent
Shusaku Egami, Takahiro Kawamura, Akihiro Fujii, Akihiko Ohsuga
IEICE Transactions on Information and Systems, Vol.J98-D, No.6, pp.992-1004, 2015 (in Japanese)
CRES: http://id.nii.ac.jp/1438/00009010/ (open access)
DOI: https://doi.org/10.1007/978-3-662-53416-8_8

We constructed a linked open data of industrial parts (screw LOD) to realize a business support agent that applies the screw LOD to the bill of materials (BOM).

International Conference (Peer-reviewed)

29. A Survey and Comparison of Activities of Daily Living Datasets in Real-life and Virtual Spaces
Swe Nwe Nwe Htun, Shusaku Egami, Ken Fukuda
The 2023 IEEE/SICE International Symposium on System Integrations (SII2023), to appear, 2023
DOI: to appear

Comparison and discussion of daily living activity datasets in real and virtual spaces.

28. Contextualized Scene Knowledge Graphs for XAI Benchmarking
Takahiro Kawamura, Shusaku Egami, Kyoumoto Matsushita, Takanori Ugai, Ken Fukuda, Kouji Kozaki
Proceedings of the 11th International Joint Conference on Knowledge Graphs (IJCKG2022), to appear, 2022
project page / data / preprint / slideshare / DOI: to appear

We developed refinement methods for the actual use of the knowledge graphs for inference and machine learning and released refined scene knowledge graphs as open data.

27. A Criminal Detection of Mystery Novel Using the Principal Components Regression Analysis Considering Co-Occurrence Words
Shuhei Katsushima, Hajime Anada, Shusaku Egami, Ken Fukuda
Proceedings of the 1st International Workshop on Knowledge Graph Reasoning for Explainable Artificial Intelligence (KGR4XAI2021) co-located with the 10th International Joint Conference on Knowledge Graphs (IJCKG2021), to appear, 2022
preprint / DOI: to appear

We proposed a criminal detection method from mystery novels using the principal components regression analysis of word vectors considering cooccurrence.

26. Ontologies of Action and Object in Home Environment towards Injury Prevention
Satoshi Nishimura, Shusaku Egami, Takanori Ugai, Mikiko Oono, Koji Kitamura, Ken Fukuda
Proceedings of the 10th International Joint Conference on Knowledge Graphs (IJCKG2021), 2021
DOI: https://doi.org/10.1145/3502223.3502239
data1 / data2

We developed the ontologies of actions and objects in the home environment, so-called Primitive Action ontology, and Home Object ontology.

25. A Framework for Constructing and Augmenting Knowledge Graphs using Virtual Space: Towards Analysis of Daily Activities
Shusaku Egami, Satoshi Nishimura, Ken Fukuda
Proceedings of the 33rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI2021), pp.1226-1230, 2021
DOI: https://doi.org/10.1109/ICTAI52525.2021.00194
code

This study proposed a framework for constructing and augmenting knowledge graphs (KGs) based on simulation results of daily living activities. Furthermore, we present several use cases using SPARQL queries and a KG embedding method.

24. VirtualHome2KG: Constructing and Augmenting Knowledge Graphs of Daily Activities Using Virtual Space
Shusaku Egami, Satoshi Nishimura, Ken Fukuda
Proceedings of the ISWC 2021 Posters, Demos and Industry Tracks co-located with 20th International Semantic Web Conference (ISWC2021), CEUR, Vol.2980, 2021
(Best Poster Award)
code / YouTube / paper (open access)

We proposed a method to construct and augment knowledge graphs (KGs) based on the simulation results of daily living activities.

23. Flight Tests for Expanding AeroMACS Coverage and Air-Ground SWIM Demonstration
Kazuyuki Morioka, Xiaodong Lu, Junichi Naganawa, Akinori Murata, Shusaku Egami, Norihiko Miyazaki, Naruto Yonemoto, Akiko Kohmura
Integrated Communications, Navigation and Surveillance Conference (ICNS2021), pp.1-8, 2021
DOI: https://doi.org/10.1109/ICNS52807.2021.9441620

We carried out flight experiments using Aeronautical Mobile Airport Communications System (AeroMACS) and System Wide Information Management (SWIM) prototype system.

22. Air/Ground SWIM Integration to Achieve Information Collaborative Environment
Xiaodong Lu, Kazuyuki Morioka, Shusaku Egami, Tadashi Koga, Yasuto Sumiya, Junichi Naganawa, Naruto Yonemoto
Air Traffic Management and Systems IV: Selected Papers of the 6th ENRI International Workshop on ATM/CNS (EIWAC2019), 2021
DOI: https://doi.org/10.1007/978-981-33-4669-7_17

The development of a practical validation system of ground taxiing experiment for A/G SWIM integration.

21. Ontology-Based Correlation Detection Among Heterogeneous Data Sets
Yuto Tsukagoshi, Shusaku Egami, Yuichi Sei, Yasuyuki Tahara, Akihiko Ohsuga
Proceedings of the Third IEEE International Conference on Artificial Intelligence and Knowledge Engineering (AIKE2020), pp.25-32, 2020
DOI: https://doi.org/10.1109/AIKE48582.2020.00014

We focused on a university campus as an example of a small organization and propose an ontology that enables the cross-sectional analysis of various data.

20. Ontology-Based Data Integration for Semantic Interoperability in Air Traffic Management
Shusaku Egami, Xiaodong Lu, Tadashi Koga, Yasuto Sumiya
Proceedings of the 14th IEEE International Conference on Semantic Computing (ICSC2020), pp.295-302, 2021
project page /
DOI: https://doi.org/10.1109/ICSC.2020.00059

We construct domain ontologies based on flight, aeronautical, and weather information exchange models. Furthermore, we confirmed the applicability of flexible searching in heterogeneous ATM data using SPARQL and ontology reasoning.

19. Report on the First Knowledge Graph Reasoning Challenge 2018 - Toward the eXplainable AI System -
Takahiro Kawamura, Shusaku Egami, Koutarou Tamura, Yasunori Hokazono, Takanori Ugai, Yusuke Koyanagi, Fumihito Nishino, Seiji Okajima, Katsuhiko Murakami, Kunihiko Takamatsu, Aoi Sugiura, Shun Shiramatsu, Shawn Zhang, Kouji Kozaki
Proceedings of the 9th Joint International Semantic Technology Conference (JIST2019), Springer LNCS, Vol.12032, pp.18-34, 2019
project page / data / arXiv / slideshare
DOI: https://doi.org/10.1007/978-3-030-41407-8_2

We organized a challenge calling for techniques that reason and/or estimate which characters are criminals while providing a reasonable explanation based on an open knowledge graph of a well-known Sherlock Holmes mystery story.

18. Enriching Geospatial Representation for Ontology-based Aviation Information Exchange
Shusaku Egami, Xiadong Lu, Tadashi Koga, Yasuto Sumiya
Proceedings of the 8th IEEE Global Conference on Consumer Electronics (GCCE2019), pp.242-243, 2019
project page /
DOI: https://doi.org/10.1109/GCCE46687.2019.9015574

We proposed a method for extending the geospatial representation of the existing aviation ontology.

17. Predicting Urban Problems: A Comparison of Graph-based and Image-based Methods
Shusaku Egami, Takahiro Kawamura, Akihiko Ohsuga
Workshop and Poster Proceedings of the 8th Joint International Semantic Technology Conference (JIST2018), CEUR, Vol.2293, pp.114-117, 2018
paper (open access)

We compared a graph-based method using knowledge graph embedding and an image-based method using convolutional neural networks (CNN) to predict urban problems such as littering.

16. Content-based Map of Science using Cross-lingual Document Embedding - A Comparison of US-Japan Funded Projects
Takahiro Kawamura, Katsutaro Watanabe, Shusaku Egami, Naoya Matsumoto, Mari Jibu
Proceedings of the 23rd International Conference on Science and Technology Indicators (STI2018), pp.385-394, 2018
project page / paper (open access)

We developed a content-based map, which converts text information, such as US-Japan funding project descriptions and paper abstracts, into multi-dimensional vectors and calculates content similarities.

15. Urban Problem LOD for Understanding the Problem Structure and Detecting Vicious Cycles
Shusaku Egami, Takahiro Kawamura, Kouji Kozaki, Akihiko Ohsuga
Proceedings of the 12th IEEE International Conference on Semantic Computing (ICSC2018), pp.186-193, 2018
DOI: https://doi.org/10.1109/ICSC.2018.00034

We proposed a method to detect root problems that lead to the vicious cycles of urban problems using SPARQL and SWRL.

14. Science Graph for characterizing the recent scientific landscape using Paragraph Vectors
Takahiro Kawamura, Katsutaro Watanabe, Naoya Matsumoto, Shusaku Egami, Mari Jibu
Proceedings of the 9th International Conference on Knowledge Capture (K-CAP2017), pp.2:1-2:8, 2017
DOI: https://doi.org/10.1145/3148011.3148018

We proposed a new content-based method of locating research projects in a multi-dimensional space using the word/paragraph embedding techniques.

13. Linked Urban Open Data Including Social Problems' Causality and Their Costs
Shusaku Egami, Takahiro Kawamura, Kouji Kozaki, Akihiko Ohsuga
Proceedings of the 7th Joint International Semantic Technology Conference (JIST2017), Springer LNCS, Vol.10675, pp.334-349, 2017
Selected for Best Paper Nominee
DOI: https://doi.org/10.1007/978-3-319-70682-5_23

We constructed Linked Open Data (LOD) that include causal relations of urban problems and the related cost information in the budget.

12. User Participatory construction of Open Hazard Data for Preventing Bicycle Accidents
Ryohei Kozu, Takahiro Kawamura, Shusaku Egami, Yuichi Sei, Yasuyuki Tahara, Akihiko Ohsuga
Proceedings of the 7th Joint International Semantic Technology Conference (JIST2017), Springer LNCS, Vol.10675, pp.289-303, 2017
DOI: https://doi.org/10.1007/978-3-319-70682-5_23

We detected locations with high possibility of bicycle accidents using user participatory sensing and published as Open Hazard Data (OHD).

11. Science Graph for characterizing the recent scientific landscape
Takahiro Kawamura, Katsutaro Watanabe, Naoya Matsumoto, Shusaku Egami, Mari Jibu
Proceedings of the 16th International Semantic Web Conference (ISWC2017) Poster & Demo Track, CEUR, Vol.1963, 2017
paper (open access)

We proposed a new content-based method of locating research projects in a multi-dimensional space using the word/paragraph embedding techniques.

10. Construction of Linked Urban Problem Data with Causal Relations using Crowdsourcing
Shusaku Egami, Takahiro Kawamura, Kouji Kozaki, Akihiko Ohsuga
Proceedings of the 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI2017), pp.814-819, 2017
DOI: https://doi.org/10.1109/IIAI-AAI.2017.189

We proposed a method for semi-automatic construction of Linked Data with the causality of urban problems, based on web pages and open government data.

9. Estimation of Spatio-temporal Missing Data for Expanding Urban LOD
Shusaku Egami, Takahiro Kawamura, Akihiko Ohsuga
Proceedings of the 6th Joint International Semantic Technology Conference (JIST2016), Springer LNCS, Vol.10055, pp.152-167, 2016
DOI: https://doi.org/10.1007/978-3-319-50112-3_12

We proposed and evaluated a method for estimating spatially missing data using computational fluid dynamics (CFD) for expanding urban LOD.

8. Linked Data Collection and Analysis Platform for Music Information Retrieval
Yuri Uehara, Takahiro Kawamura, Shusaku Egami, Yuichi Sei, Yasuyuki Tahara, Akihiko Ohsuga
Proceedings of the 6th Joint International Semantic Technology Conference (JIST2016), Springer LNCS, Vol.10055, pp.127-135, 2016
DOI: https://doi.org/10.1007/978-3-319-50112-3_10

We represented the music data with Linked Data, which are in a format suitable for computer processing, and also link data fragments to each other.

7. Estimation of Spatial Missing Data for Expnading Urban LOD
Shusaku Egami, Takahiro Kawamura, Akihiko Ohsuga
Workshop and Poster Proceedings of the 6th Joint International Semantic Technology Conference (JIST2016), CEUR, Vol.1741, pp.82-85, 2016
paper (open access)

We proposed and evaluated a method for estimating spatially missing data using computational fluid dynamics (CFD) for expanding urban LOD.

6. Linked Data Collection and Analysis Platform of Audio Features
Yuri Uehara, Takahiro Kawamura, Shusaku Egami, Yuichi Sei, Yasuyuki Tahara, Akihiko Ohsuga
Workshop and Poster Proceedings of the 6th Joint International Semantic Technology Conference (JIST2016), CEUR, Vol.1741, pp.78-81, 2016
paper (open access)

We represented the music data with Linked Data, which are in a format suitable for computer processing, and also link data fragments to each other.

5. Building Urban LOD for Solving Illegally Parked Bicycles in Tokyo
Shusaku Egami, Takahiro Kawamura, Akihiko Ohsuga
Proceedings of the 15th International Semantic Web Conference (ISWC2016), Springer LNCS, Vol.9982, pp.291-307, 2016
DOI: https://doi.org/10.1007/978-3-319-46547-0_28

We proposed a method for sustainably building urban LOD to solve the illegally parked bicycle problem and applied them to Tokyo and other urban areas.

4. Schema Design of Illegally Parked Bicycles LOD
Shusaku Egami, Takahiro Kawamura, Yuichi Sei, Yasuyuki Tahara, Akihiko Ohsuga
Proceedings of the 5th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI2016), pp.692-697, 2016
DOI: https://doi.org/10.1109/IIAI-AAI.2016.226

We proposed a schema design of illegally parked bicycles LOD and a methodology of designing LOD schema.

3. Visualization of Open Urban Data for Illegally Parked Bicycles
Shusaku Egami, Takahiro Kawamura, Yuichi Sei, Yasuyuki Tahara, Akihiko Ohsuga
CompleXity: Technology for Complex Urban Systems in the 49th Hawaii International Conference on System Sciences (HICSS-49), 2016

We built an ecosystem that generates Open Urban Data in Link Data format while complementing missing attribute values.

2. Building of Industrial Parts LOD for EDI - A Case Study -
Shusaku Egami, Takahiro Kawamura, Akihiro Fujii, Akihiko Ohsuga
Proceedings of the 4th Joint International Semantic Technology Conference (JIST2014), Springer LNCS, Vol.8943, pp.146-161, 2014
DOI: https://doi.org/10.1007/978-3-319-15615-6_11

We built industrial parts Linked Open Data (LOD), which we called "N-ken LOD" based on a screw product code system (N-ken Code). Then we linked it to external datasets like DBpedia and built product supplier relations to support the EDI.

1. EDI support with LOD
Akihiro Fujii, Shusaku Egami, Hiroyasu Shimizu
Proceedings of the JIST 2013 Joint International Workshop: 2013 Linked Data in Practice Workshop (LDPW2013) and the 1st Workshop on Practical Application of Ontology for Semantic Data Engineering (PAOS2013), CEUR, Vol.1192, pp.27-32, 2013
paper (open access)

We discussed perspective in utilizing LOD for variety of EDI requirements.

Book

11. Chapter 11 - Mapping Science based on research content similarity -
Takahiro Kawamura, Katsutaro Watanabe, Naoya Matsumoto, Shusaku Egami
Scientometrics, InTechOpen, ISBN 978-1-78923-306-3, 2018
project page /
DOI: http://doi.org/10.5772/intechopen.77067 (open access)

This article proposes a content-based method of locating research articles/projects in a multi-dimensional space using word/paragraph embedding.

Awards

Work Experience

Academic Background

Committee Member

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Hobby

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