The 21st International Conference on Knowledge Engineering and Knowledge Management concerns all aspects of eliciting, acquiring, modeling and managing knowledge, and the role of knowledge in the construction of systems and services for the semantic web, knowledge management, e-business, natural language processing, intelligent information integration, and so on.
The special theme of EKAW 2018 is “Knowledge and AI”. We are indeed calling for papers that describe algorithms, tools, methodologies, and applications that exploit the interplay between knowledge and Artificial Intelligence techniques, with a special emphasis on knowledge discovery.
EKAW 2018 will put a special emphasis on the importance of Knowledge Engineering and Knowledge Management with the help of AI as well as for AI.
Proceedings
The proceedings of the research track will be published by Springer Verlag in the Lecture Notes in Artificial Intelligence series.
The authors of selected best papers will be invited to submit an extended version of their manuscript to a special issue of the Semantic Web Journal by IOS Press.
Best paper award
Research and in-use papers are eligible for the Bob Wielinga Best Paper Award sponsored by Springer that will award a prize of 1,000 euros to the best paper of the main track.
Topics of interest
EKAW 2018 welcomes papers dealing with theoretical, methodological, experimental, and application-oriented aspects of knowledge engineering and knowledge management.
In particular, but not exclusively, we solicit papers about methods, tools and methodologies on the following topics:
- Knowledge and AI
- AI-based knowledge engineering and management
- Natural Language Processing and knowledge acquisition
- Knowledge acquisition for AI
- Intelligent knowledge evolution, maintenance, and repair
- Managing compliance between knowledge and data
- Managing Multi-media knowledge
- Machine Learning and the knowledge lifecycle
- Combining learning knowledge from data and from humans
- Modeling learned and conceptual knowledge together
- Lessons learned from case studies
- Adoption of techniques that exploit knowledge and AI
- Evaluation of techniques that exploit knowledge and AI
- Knowledge discovery
- Mining patterns and association rules
- Mining complex data: numbers, sequences, trees, graphs
- Formal Concept Analysis and extensions
- Numerical data mining methods and knowledge processing
- Mining the web of data for knowledge construction
- Text mining and ontology engineering
- Classification and clustering for knowledge management
- Knowledge Management
- Methodologies and tools for knowledge management
- Knowledge sharing and distribution, collaboration
- Best practices and lessons learned from case studies
- Provenance and trust in knowledge management
- Methods for accelerating take-up of knowledge management technologies
- Corporate memories for knowledge management
- Knowledge evolution, maintenance and preservation
- Web 2.0 technologies for knowledge management
- Incentives for human knowledge acquisition (e.g. games with a purpose)
- Knowledge Engineering and Acquisition
- Tools and methodologies for ontology engineering
- Ontology design patterns
- Ontology localisation
- Ontology alignment
- Knowledge authoring and semantic annotation
- Knowledge acquisition from non-ontological resources (thesauri, folksonomies, etc.)
- Semi-automatic knowledge acquisition, e.g., ontology learning
- Mining the Semantic Web and the Web of Data
- Ontology evaluation and metrics
- Uncertainty and vagueness in knowledge representation
- Dealing with dynamic, distributed and emerging knowledge
- Social and Cognitive Aspects of Knowledge Representation
- Similarity and analogy-based reasoning
- Knowledge representation inspired by cognitive science
- Synergies between humans and machines
- Knowledge emerging from user interaction and networks
- Knowledge ecosystems
- Expert finding, e.g., by social network analysis
- Trust and privacy in knowledge representation
- Collaborative and social approaches to knowledge management and acquisition
- Crowdsourcing in knowledge management
- Applications in specific domains such as
- eGovernment and public administration
- Life sciences, health and medicine
- Humanities and Social Sciences
- Automotive and manufacturing industry
- Cultural heritage
- Digital libraries
- Geosciences
- ICT4D (Knowledge in the developing world)
Type of papers
We will accept different types of papers. The papers will all have the same status and follow the same formatting guidelines in the proceedings but will receive special treatment during the reviewing phase. In particular, each paper type will be subject to its own evaluation criteria. The Programme Committee will also make sure that there is a reasonable balance of the paper types accepted. At submission time the paper has to be clearly identified as belonging to one of the following categories.
- Research papers: These are “standard” papers presenting a novel method, technique or analysis with appropriate empirical or other types of evaluation as a proof-of-concept. The main evaluation criteria here will be originality, technical soundness and validation.
- In-use papers: Here we are expecting papers describing applications of knowledge management and engineering in real environments. Applications need to address a sufficiently interesting and challenging problem on real-world datasets, involving many users, etc. The focus is less on the originality of the approach and more on presenting systems that solve a significant problem while addressing the particular challenges that come with the use of real-world data. Evaluations are essential for this type of paper and should involve a representative subset of the actual users of the system.
- Position papers: We invite researchers to also publish position papers, which describe novel and innovative ideas. Position papers may also comprise an analysis of currently unsolved problems, or review these problems from a new perspective, in order contribute to a better understanding of these problems in the research community. We expect that such papers will guide future research by highlighting critical assumptions, motivating the difficulty of a certain problem or explaining why current techniques are not sufficient, possibly corroborated by quantitative and qualitative arguments.
Important dates
- Abstract deadline:
July 2nd, 2018 - Submission deadline:
July 12th, 2018(deadline extension)
- Notification of acceptance:
August 31st, 2018 - Camera-ready paper: September 12th, 2018
- Conference days: November 13th-16th, 2018
All submission deadlines are 23:59:59 Hawaii Time.
Submissions
Pre-submission of abstracts is a strict requirement. All papers and abstracts have to be submitted electronically via EasyChair.
All submissions for research, in-use, and position papers must be in English, and no longer than 15 pages. Papers that exceed this limit will be rejected without review.
Submissions must be in PDF, formatted in the style of the Springer Publications format for Lecture Notes in Computer Science (LNCS). For details on the LNCS style, see Springer’s Author Instructions.
Organization
General chair
- Amedeo Napoli (CNRS, France)
- Yannick Toussaint (Université de Lorraine, France)
Program chairs
- Catherine Faron Zucker (Université Nice Sophia Antipolis, France)
- Chiara Ghidini (Fondazione Bruno Kessler, Italy)
