Workshops and tutorials

List of accepted workshops and tutorials

2nd International Workshop on Capturing Scientific Knowledge
Martine de Vos, Daniel Garijo

SciKnow is a full day workshop to bring together researchers interested in representing and capturing knowledge about science so that it can be used by intelligent systems to support scientific research and discovery.

Machine Reading
Bruce Porter, Peter Clark, Ken Barker

Machine Reading is a half day workshop in which participants will discuss ways to develop new capabilities in macro- and micro-reading, in particular to extract useful representations of text (be they symbolic, neural, or a hybrid) that enable, for example, automated reasoning to answer non-trivial questions.

Semantic data mining for knowledge acquisition
Agnieszka Lawrynowicz

This half day tutorial intends to provide a synthetic, unifying view on semantic data mining and its application to knowledge acquisition. The tutorial also specifically aims to present major research challenges arising from pecularities of semantic data mining (proper consideration of the semantics of background knowledge, dealing with Open World Assumption, semantic similarity measures).

DOing REusable MUSical data (DOREMUS)
(Pasquale Lisena, Raphael Troncy)

The aim of this half-day tutorial is to provide in-depth explanations of the DOREMUS model (and its underlying foundations, CIDOC-CRM and FRBRoo) as well as the necessary controlled vocabularies. We will demonstrate how real data coming from musical libraries can be converted to this model and be transformed to be compliant to for various consumption scenarios. The entire DOREMUS tools chain will be presented (e.g. tools for reconciling large multilingual knowledge graphs). We will illustrate how the DOREMUS data can be consumed through various applications including an exploratory search engine and music recommender systems. Finally, we will propose several hands-on for the audience to play with the DOREMUS data.

Hybrid techniques for knowledge-based NLP: Knowledge graphs meet machine learning and all their friends
(Jose-Manuel Gomez-Perez, Ronald Denaux, Daniel Vila, Carlos Badenes)

This half-day tutorial will cover the foundations and modern practical applications of knowledge-based and statistical methods, techniques and models and their combination for exploiting large document corpora. We will first focus on the foundations of many of the techniques that can be used for this purpose, including knowledge graphs, word embeddings, neural network methods, probabilistic topic models, and will then describe how a combination of these techniques is being used in practical applications and commercial projects where the instructors are currently involved.