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{{Paper
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|authors=Nam D. Vo,O-Joun Lee,Khac-Hoai Nam Bui,Hae Gyun Lim,Hyeon-Ju Jeon,Phuong-Mai Nguyen,Jin-Taek Kim,Bui Quang Tuyen,Jason J. Jung,Thuy Anh Vo
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https://ceur-ws.org/Vol-3026/preface.pdf
Computing4Human 2021: The 2nd International
Conference on Human-centered Artificial Intelligence⋆
Nam D. Vo1 , O-Joun Lee2 , Khac-Hoai Nam Bui3 , Hae Gyun Lim4 ,
Hyeon-Ju Jeon5 , Phuong-Mai Nguyen6 , Jin-Taek Kim7 , Bui Quang Tuyen8 ,
Jason J. Jung9 , and Thuy Anh Vo10⋆⋆
1 The University of Danang, Da Nang, Viet Nam
vdnam@ac.udn.vn
2 The Catholic University of Korea, Bucheon-si, Republic of Korea
ojlee@catholic.ac.kr
3 Viettel Cyberspace, Viettel Group, Hanoi, Viet Nam
hoainam.bk2012@gmail.com
4 Pukyong National University, Busan, Republic of Korea
hglim@pknu.ac.kr
5 Korea Institute of Atmospheric Prediction Systems, Seoul, Republic of Korea
hjjeon@kiaps.org
6 International School, Vietnam National University, Hanoi, Viet Nam
mainp@vnu.edu.vn
7 Pohang University of Science and Technology, Pohang-si, Republic of Korea
jintaek@postech.ac.kr
8 Viettel Academy, Viettel Group, Hanoi, Viet Nam
tuyenbq.ueb@gmail.com
9 Chung-Ang University, Seoul, Republic of Korea
j3ung@cau.ac.kr
10 University of Economics, The University of Danang, Da Nang, Viet Nam
vothuyanh@yahoo.com
Abstract. The 2nd international conference on human-centered artificial intel-
ligence (Computing4Human) is hosted by the University of Economics, The
University of Danang, on the 28th of October 2021. This conference tackled
various research areas: the Computational Humanities and Social Sciences, Smart
Infrastructure, Smart Healthcare, Secure and Green IoT Communications, Explain-
able Recommendation and Retrieval, and Business Intelligence. We collected 35
papers, which were fully refereed and underwent a single-blind review process by
at least three reviewers. Finally, 26 papers have been published for six technical
tracks.
⋆ Copyright © by the paper’s authors. Use permitted under Creative Commons License Attribution
4.0 International (CC BY 4.0). In: N. D. Vo, O.-J. Lee, K.-H. N. Bui, H. G. Lim, H.-J. Jeon,
P.-M. Nguyen, B. Q. Tuyen, J.-T. Kim, J. J. Jung, T. A. Vo (eds.): Proceedings of the 2nd
International Conference on Human-centered Artificial Intelligence (Computing4Human 2021),
Da Nang, Viet Nam, 28-October-2021, published at http://ceur-ws.org
⋆⋆ Corresponding author.
2 Vo et al.
Keywords: Computational Humanities and Social Sciences, Smart Infrastruc-
ture, Smart Healthcare, Secure and Green IoT Communications, Explainable
Recommendation and Retrieval, Business Intelligence.
1 Introduction
The 2nd international conference on human-centered artificial intelligence (Comput-
ing4Human) will be held in Danang, Vietnam (and virtual conference), which is or-
ganized by the University of Da Nang. Computing4Human begun initially under the
name of the international workshop on computational humanities and social sciences
in 2020 [12]. The rapid development of artificial intelligence (AI) techniques and their
applications has remarkably changed how we live and how our societies operate. At
the last event, we have focused on these changes in the humanities and social sciences
fields. The last event covered embracing domain knowledge of humanities and social
sciences fields into AI methodologies [9,11], solving research issues in these fields by
employing AI techniques [32,16], and social and humane issues caused by the novel AI
techniques and applications [10]. However, the influence of AI’s advent is not easy to be
investigated by only perspectives adopted from the humanities and social sciences. For
example, we need city planning experts to discuss further research directions of smart
infrastructure or data-driven city planning, and smart healthcare research is difficult to
be conducted without comments from medical doctors.
Therefore, this year, we have aimed at gathering scholars who deal with AI tech-
niques in various domains. We have removed boundaries of the area of interest of this
conference and extended the area to artificial intelligence methodologies for every user-
intimate (human-centered) application and novel issues caused by the advent of AI
techniques in every domain. The main purpose of Computing4Human 2021 has been to
search for unexplored areas of human-centered AI applications and develop advanced
methodologies for these areas by encouraging open discussions between scholars in AI
and researchers with domain expertise. In this regard, we founded technical tracks to
cover the various domains of human-centered AI applications.
2 Technical Tracks
Computing4Human 2021 has dealt with six research areas: the Computational Human-
ities and Social Sciences, Smart Infrastructure, Smart Healthcare, Secure and Green
IoT Communications, Explainable Recommendation and Retrieval, and Business Intelli-
gence. Technical tracks have been organized in each research area, and the track chairs
operated evaluation and selection processes for their submissions. Totally, we collected
35 papers and have published 26 papers, which were fully refereed and underwent a
single-blind review process by at least three reviewers.
2.1 Computational Humanities and Social Sciences
Jin-Taek Kim, Eun-Soon You, and O-Joun Lee founded this track on Computing4Human
2020, and Kim and You have mainly hosted it this year. This track has aimed to discuss
Computing4Human 2021 3
novel research directions and contributions belonging to intersections between the two
research communities (i.e., humanities and social sciences and artificial intelligence).
Thereby, track chairs attempted to gather various opinions from different research
areas, including computer science, computational linguistics, digital humanities, political
science, economic, and so on.
Digital humanity studies were focused on multimedia content. Hochang Kwon [14]
discussed political and aesthetic possibilities of interactive documentaries, Lee et al. [17]
analyzed usages and functions of shot-types in movies, and Han et al. [5] conducted a
case study for metaverse platform as a novel recreation culture. Also, Kwak et al. [13]
presented a comparative study for conversational virtual agents and robots.
There have also been studies for applying data analysis techniques to issues in social
sciences. Regarding smart governance, Vo and Le [30] analyzed e-government adoption
in Vietnam. In a more specific case, Nguyen et al. [20] discussed factors that influence
the behavioral intention of citizens for sorting solid waste. For the education sector, Chuc
and Ngoc [4] analyzed laptop usage behaviors of students. In addition, Tran and Nguyen
[25] have proposed a machine learning model for predicting employment periods of
workers by focusing on business administration.
2.2 Smart Infrastructure
Hongsuk Yi and Khac-Hoai Nam Bui have extended coverage of Computing4Human
2021 to smart infrastructure. Recently, the emerging technologies on the Internet of
Things (IoT), cloud/edge computing, and data analytics have enabled the realization
of cyber-physical systems. Therefore, the trend of “IoT meetings AI” has become an
emergent research topic for future smart cities and infrastructures. This track encourages
authors from academia and industry to submit new research results about technologi-
cal innovations and novel applications based on AI-powered IoT for smart cities and
infrastructure.
Vuong and Tran [31] raised a fundamental issue for whether artificial intelligence
techniques contribute to innovation and value creation in the tourism industry. We have
to deliberate this issue regarding a ripple effect of technology development on the whole
community. To et al. [24] presented a more practical study for smart city applications.
To solve the lack of labeled data, they attempted to generate a labeled image dataset by
deploying object detectors on edge devices. A few studies dealt with weather forecasting,
which is getting significant due to climate change. Ho et al. [6] attempted to predict
rainfall in Vietnam, and An et al. [1] have proposed a novel neural network optimizer for
emulating atmospheric phenomena.
2.3 Smart Healthcare
Computing4Human 2021 has launched a new technical track on smart healthcare with
Hae Gyun Lim. This track aimed to explore the potential applications of novel AI
technologies (big-data analytics, management of chorionic diseases, medical devices,
medical imaging, and integration of AI and internet of things) to enhance the traditional
healthcare strategies for supporting the development of the emerging platform and
new healthcare medical device for innovating the healthcare ecosystem. Thus, the
4 Vo et al.
track committee has invited research contributions ranging from diagnostic imaging
interpretation, robot-assisted surgery systems, cybersecurity, fraud detection, health
monitoring, drug creation technology, among others.
Truong and Truong-Dinh [27] discussed usages of wearable healthcare technology
with a case study of Vietnam. Also, they analyzed factors that affect users’ usage intention
of wearable healthcare devices. On the automated diagnosis, Pham et al. [7] have
proposed a method for detecting children with ADHD (Attention Deficit Hyperactivity
Disorder) by analyzing their EEG signals.
2.4 Secure and Green IoT Communications
The number of Internet-of-thing (IoT) devices, such as vehicles, unmanned aerial vehicles
(UAVs), and sensors, has been increasing rapidly. Therefore, there is a requirement
for huge energy consumption for massive IoT networks. In addition, the beyond fifth
generation and sixth generation (B5G/6G) networks will be expected to handle thousands
of times more data than current networks. Tri M. Ngo, Mai T. P. Le, Tuan D. Dao, and
Hieu V. Nguyen have launched the secure and green IoT communication track to discuss
these issues. On this track, Hung Quang Nguyen [19] has proposed a novel identity-based
cryptography algorithm to resolve the security issues on smart home applications.
2.5 Explainable Recommendation and Retrieval
Recommendation and retrieval services are necessary for human beings in modern soci-
eties. Despite the erstwhile development, methodologies for enhancing the persuasibility
of these services have not been significantly improved. Therefore, Nam D. Vo and O-Joun
Lee have founded this track to gather novel approaches and ideas for the explainable
recommendation and retrieval systems.
Jeon et al. [8] have proposed a representation learning model for citation relations
in bibliographic networks. Their model, which is a modification of transformer, can
consider the context of citations. The contextual representations of citations can be
applied to explainable recommendation and retrieval in academic services. Nham Cao
Thi [23] has proposed an explainable prediction model for churn of bank customers.
For generating explanations, a state-of-the-art method, Shapley Additive exPlanations
(SHAP), was employed. Quynh and Dung [22] also attempted to predict customers’
behaviors and analyze feature importance. Dinh-Van Phan [21] attempted to model
relationships between civil servants using knowledge graphs and explain their kinship.
Additionally, Nguyen et al. [18] attempted to predict factors that affect the readiness of
big data adoptions.
2.6 Business Intelligence
The conventional business intelligence systems aim to improve companies’ performances
in various aspects, such as marketing, human resource management, and production.
Artificial intelligence techniques can expand the purposes to more qualitative factors: cus-
tomer satisfaction, company identity, social responsibility, and sustainable growth. This
Computing4Human 2021 5
point is critical for modern business environments that focus on future values and ESG
(environmental, social, and governance) rather than short-term profits. Therefore, Duc-
Quynh Tran and Phuong-Mai Nguyen have founded this track on Computing4Human
2021 to discuss future directions in AI-enhanced business intelligence.
Trinh et al. [2] conducted an interesting study for analyzing the impact of social media
celebrities on their followers’ purchase intention. Similarly, Chu et al. [3] discussed the
effects of digital content marketing of e-commerce platforms on purchase intention, in
the focus of customers’ passive use. Le et al. [15] also dealt with e-commerce. They
propose a novel broker-based trade allocation method to enable agent-based e-commerce
platforms to consider the constraints of buyers and sellers.
A few studies dealt with stock markets. Tran et al. [26] have proposed a novel
stock market prediction method based on financial news analysis. Tung et al. [28] have
proposed a sentiment analysis model (PhoBERT) to classify news headlines related to
stock markets according to sentiment. Additionally, Tuyen et al. [29] presented a case
study for the digitalization of corporate training of a well-known company, Viettel group.
3 Acknowledgments
3.1 Sponsors & Supporters
The 2nd International Conference on Human-centered Artificial Intelligence (Comput-
ing4Human 2021) is grateful for the support received from its sponsors:
– The Catholic University of Korea, Republic of Korea
– International School, Vietnam National University Hanoi, Vietnam
– Chung-Ang University, Republic of Korea
– Pohang University of Science and Technology, Republic of Korea
– Viettel Academy, Viettel Group, Vietnam
– National Economics University, Vietnam
3.2 Organizing Committee
Researchers in various institutions, including both of the academic and industrial, have
been contributed to Computing4Human 2021 as organizing committee members and
program committee members.
General Co-Chairs
– Thuy Anh Vo, University of Economics - The University of Danang, Vietnam
– Thanh Le Trung, Vietnam National University Hanoi - International School, Vietnam
– Jin-Taek Kim, Pohang University of Science and Technology, Republic of Korea
– Jason J. Jung, Chung-Ang University, Republic of Korea
Program Committee Chair
– O-Joun Lee, The Catholic University of Korea, Republic of Korea
6 Vo et al.
Local Chairs
– Nam D. Vo, The University of Danang, Vietnam
Track Chairs
– Jin-Taek Kim, Pohang University of Science and Technology, Republic of Korea
– Hae Guyn Lim, Pukyong National University, Republic of Korea
– Hongsuk Yi, Korea Institute of Science and Technology Information, Republic of
Korea
– Khac-Hoai Nam Bui, Viettel Group, Vietnam
– Eun-Soon You, Inha University, Republic of Korea
– Tri M. Ngo, University of Science and Technology, University of Danang, Vietnam
– Mai T. P. Le, University of Science and Technology, University of Danang, Vietnam
– Tuan D. Dao, University of Science and Technology, University of Danang, Vietnam
– Hieu V. Nguyen, University of Science and Technology, University of Danang,
Vietnam
– Duc-Quynh Tran, International School, Vietnam National University Hanoi, Vietnam
– Phuong Mai Nguyen, International School, Vietnam National University Hanoi,
Vietnam
Publicity Chairs
– Hyeon-Ju Jeon, Korea Institute of Atmospheric Prediction Systems, Republic of
Korea
– Vu Dang Thinh, Sen Do Joint Stock Company, Vietnam
Website Chair
– Sojung An, Korea Institute of Atmospheric Prediction Systems, Republic of Korea
Program Committee Members
– Jason J. Jung, Chung-Ang University, Republic of Korea
– O-Joun Lee, The Catholic University of Korea, Republic of Korea
– Jin-Taek Kim, Pohang University of Science and Technology, Republic of Korea
– Hae Guyn Lim, Pukyong National University, Republic of Korea
– Hongsuk Yi, Institute of Science and Technology Information, Republic of Korea
– Khac-Hoai Nam Bui, Viettel Group, Vietnam
– Eun-Soon You, Inha University, Republic of Korea
– Nam D. Vo, University of Danang, Vietnam
– Dien Tuan Le, University of Danang, Vietnam
– Dinh Van Phan, University of Danang, Vietnam
– Thanh Ha Hoang, University of Danang, Vietnam
– Tri M. Ngo, University of Danang, Vietnam
– Mai Le, University of Danang, Vietnam
Computing4Human 2021 7
– Tuan D. Dao, University of Danang, Vietnam
– Hieu V. Nguyen, University of Danang, Vietnam
– Quynh D. Tran, Vietnam National University Hanoi, Vietnam
– Mai P. Nguyen, Vietnam National University Hanoi, Vietnam
– Sojung An, Korea Institute of Atmospheric Prediction Systems, Republic of Korea
– Hyeon-Ju Jeon, Korea Institute of Atmospheric Prediction Systems, Republic of
Korea
– Tri-Hai Nguyen, Chung-Ang University, Republic of Korea
– Jeong-Ryun Ko, Chung-Ang University, Republic of Korea
– Ji-Hyeon Ahn, Chungkang College of Cultural Industries, Republic of Korea
– Heesoo Kim, Pukyong National University, Republic of Korea
– Yeonggeun Kim, Pukyong National University, Republic of Korea
– Jinhee Yoo, Pukyong National University, Republic of Korea
– Hyeon-Gyeong Seo, Chungkang College of Cultural Industries, Republic of Korea
Acknowledgment
This work was supported by the National Research Foundation of Korea (NRF) grant
funded by the Korea government (MSIP) (NRF-2020R1A2B5B01002207,
NRF-2021R1I1A1A01060302).
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