ICWE2021 – Workshop Papers
Workshop 1. International Workshop on Big data driven Edge Cloud Services (BECS)
Edge clouds are becoming an important computing platform for collecting and processing big data as the low-latency and highly reliable communications technology such as 5G, and Internet of Things (IoT) are developed and deployed. In this workshop, we are developing technologies for efficiently collecting and processing various types of big data in edge cloud environments in real time. In addition, we are developing a framework for building big data service applications in a highly reliable and usable manner.
- In-Young Ko (Korea Advanced Institute of Science and Technology (KAIST), South Korea)
- Abhishek Srivastava (Indian Institute of Technology Indore (IIT Indore), India)
- Michael Mrissa (InnoRenew CoE, University of Primorska, Slovenia)
Workshop 2. International Workshop on Web Engineering in Education (WEE2021)
“Web Engineering in Education” will be organized as part of Workshop at the International Conference “The International Conference on Web Engineering” (ICWE 2021) and invites to participate in discussions on Web-related engineering in education and its various aspects at all levels and in all contexts.
The workshop is aimed at discussing with the professional community the latest achievements in the field of web engineering, the development of intelligent educational resources, web engineering training, and the application of web engineering achievements in the field of education. To develop possible directions for further development of the sphere of education by introducing web engineering capabilities in the following directions:
- Development of intelligent educational resources based on web engineering.
- Monitoring of the digital educational trail.
- How to train individual disciplines in web engineering.
The Workshop may address a variety of topics, not limited to including innovative research in the following areas:
- tools for teaching assistance (intellectual educational resources),
- development of competencies and demand in the labour market,
- course content,
- curriculum structure,
- training methods,
- diagnostic, monitoring, evaluation methods,
- assessments of alternative approaches
- Financial University under the Government of the Russian Federation, Faculty of Information Technology and Big Data Analysis, Department of Data Analysis and Machine Learning, Russian Federation, Moscow.
- Institute of Digital Education, Moscow City Pedagogical University, Moscow, Russia.
- Abay Kazakh National Pedagogical University, Institute of Mathematics, Physics and Computer Science, Almaty, Kazakhstan.
- Institute of Electrical Engineering Slovak Academy of Sciences (IEE SAS), Bratislava, Slovakia. Frank Reidy Research Center for Bioelectrics Old Dominion University, Norfolk, Virginia, USA.
Workshop 3. International workshop on knowledge discovery on the web (KDWEB2021)
Knowledge Discovery is an interdisciplinary area focusing upon methodologies for identifying valid, novel, potentially useful and meaningful patterns from such data, and currently is widespread in numerous fields, including science, engineering, healthcare, business, and medicine. Recently, the rapid growth of social networks and online services entailed that Knowledge Discovery approaches focused on the World Wide Web (WWW), whose popular use as global information system led to a huge amount of digital data. KDWeb 2021 is focused on the field of Knowledge Discovery from digital data, with particular attention for Data Mining, Machine Learning, and Information Retrieval methods, systems, and applications. KDWeb 2020 is aimed at providing a venue to researchers, scientists, students, and practitioners involved in the fields of Knowledge Discovery on Data Mining, Information Retrieval, and Semantic Web, for presenting and discussing novel and emerging ideas. KDWeb 2021 will contribute to discuss and compare suitable novel solutions based on intelligent techniques and applied in real-world applications.
The workshop welcomes submissions of fresh investigations concerning experimental and applied studies on web Knowledge Discovery. The topics include but are not limited to:
- Big Data on the Web
- Data Mining
- Deep Learning on the Web
- Feature Selection and Extraction of Web data
- Hierarchical Categorization of Web data
- Knowledge Discovery
- Linked Web Data
- Machine Learning applications on the Web
- Open Web Data
- Semantic Web
- Semantics and Ontology Engineering for Web applications
- Social Media Mining
- Social Media Measures and applications
- Text Categorization on the Web
- Text Mining for Web applications
- Web data Mining
- Web Information Filtering and Retrieval
- Web Personalization and Recommendation
- Giuliano Armano (Department of Mathematics and Computer Science -University of Cagliari, Italy)
- Matteo Cristani (Department of Computer Science -University of Verona, Italy)
- Claudio Tomazzoli (CITERA Interdepartmental Centre, Sapienza University of Rome, Italy)