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QEKGraph 2017 : 1st International Workshop on Quality Engineering Meets Knowledge Graph, co-located with International Conference on K-CAP 2017 | |||||||||||||||
Link: http://qekgraph.kmi.open.ac.uk/ | |||||||||||||||
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Call For Papers | |||||||||||||||
1st International Workshop on Quality Engineering Meets Knowledge Graph- QEKGraph 2017
**Submission deadline: Thursday, September 28, 2017 23:59 Hawaii time** Workshop Date: December 4, 2017 (TBC) Venue: Austin, Texas, United States (co-located with K-CAP 2017) Twitter: @qekgraph Site: http://qekgraph.kmi.open.ac.uk/index.html Workshop chairs: - Shuangyan Liu - The Open University, United Kingdom - Alessandro Adamou - The Open University, United Kingdom - Nandana Mihindukulasooriya - Universidad Politécnica de Madrid, Spain # DESCRIPTION A knowledge graph is any graph-based knowledge base, which represents a large network of entities, their semantic types (e.g. a Person or an Organisation), properties (e.g. the name and birth date of a person), and relationships between entities such as a person working in an organisation. Academic research communities, as well as industrial stakeholders, have constructed a number of large-scale knowledge graphs in recent years such as DBpedia, YAGO, Freebase, Wikidata, Google Knowledge Graph, Microsoft Satori, Facebook Entity Graph, Yahoo! Knowledge Graph and others. They are intensively used in different application scenarios such as search, question answering, natural language processing, data integration and analytics, and for specialised areas such as digital humanities, business, life science and more. However, due to the diversity of data sources and limitations of present knowledge extraction methods, most knowledge graphs face a variety of quality issues such as noise and vague data, inconsistency, inaccurate and out-of-date data, incomplete information, and poor interlinking between KGs. To facilitate wide adoption and advanced usage, it is crucial to ensure the quality of knowledge graphs. There are still big gaps between present state of quality engineering techniques and high quality KGs and their effective applications. Therefore, this workshop aims to address not only the challenges and state-of-the-art solutions in quality assessment and improvement for knowledge graphs, but also challenges for effectively employing reliable KGs in different domains. QEKGraph welcomes original research contributions crossing Data Quality and knowledge graph management and consumption. Scholars who have conducted research or developed impactful applications are invited to submit full papers with appropriately evaluated contributions. QEKGraph also welcomes vision/position papers on novel challenges or approaches to existing problems (short papers). Topics on which potential submitters are invited to contribute include, but are not limited to: - Quality issues in knowledge graphs - Quality assessment metrics and measures - Representation of quality assessment results - Data cleaning and knowledge graphs - Outlier detection in knowledge graphs - Triple classification and ranking - Trust and provenance of knowledge graphs - Data integration and quality control - Evaluation of quality of links in the Web of Data - Evaluation of link prediction methods - Evaluation benchmark and datasets - Multilingual knowledge graphs and quality control - Quality assessment at scale - Crowdsourcing and knowledge graph quality - Quality of specialised knowledge graphs - Trust and reliability of digital humanities and social science data - Advancing education with data quality engineering Submissions in all the categories mentioned above (full or short papers) will be peer-reviewed by acknowledged researchers familiar with both scientific communities. Accepted papers will be published as online proceedings courtesy of CEUR-WS.org. # IMPORTANT DATES Submission deadline: Thursday, September 28, 2017* Notification to authors: Friday, October 13, 2017* Camera-ready due on: Sunday, October 22, 2017* Workshop day: Monday, December 4, 2017 - to be confirmed (*) All deadlines are 23:59 Hawaii time # SUBMISSION INSTRUCTIONS All papers must represent original and unpublished work that is not currently under review. Papers will be evaluated according to their significance, originality, technical content, style, clarity, and relevance to the workshop. We welcome the following types of contributions: - Full papers (up to 6 pages) - Short papers (up to 4 pages) All submissions must be PDF documents written in English and formatted according to ACM SIG Proceedings guidelines [https://www.acm.org/publications/proceedings-template]. Papers are to be submitted through the Easychair Conference Management System [https://easychair.org/conferences/?conf=qekgraph2017]. Page limits are inclusive of references and appendices, if any. # PROGRAM COMMITTEE - Riccardo Albertoni, Istituto per la Matematica Applicata e Tecnologie Informatiche "Enrico Magenes", Italy - Mathieu d’Aquin, Insight Centre Galway, Ireland - Helena Bermúdez-Sabel, Universidad de Educación a Distancia (UNED), Spain - Oscar Corcho, Universidad Politécnica de Madrid, Spain - Mariana Curado Malta, Polythecnic of Oporto, Portugal - Marilena Daquino, Digital Humanities, University of Bologna, Italy - Jeremy Debattista, Adapt Centre, Trinity College Dublin, Ireland - Wassim Derguech, Insight Centre Galway, Ireland - Anastasia Dimou, Ghent University - IMEC, Belgium - Lisa Ehrlinger, Johannes Kepler University, Austria - Raúl García-Castro, Universidad Politécnica de Madrid, Spain - Oktie Hassanzadeh, IBM Thomas J. Watson Research Center, United States - Sangha Nam, KAIST, Korea - Francesco Osborne, The Open University, UK - Mariano Rico, Universidad Politécnica de Madrid, Spain - Mariano Rodriguez-Muro, IBM Thomas J. Watson Research Center, United States - Cristina Sarasua, Universität Koblenz-Landau, Germany - Bahar Sateli, Concordia University, Canada - Boris Villazon-Terrazas, Fujitsu Laboratories of Europe, Madrid, Spain - Amrapali Zaveri, Maastricht University, The Netherlands |
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