- From: Dagmar Gromann <dgromann@iiia.csic.es>
- Date: Wed, 10 May 2017 15:59:50 +0200 (CEST)
- To: semantic-web@w3.org
- Cc: Thierry Declerck <declerck@dfki.de>
- Message-ID: <1760952617.33942.1494424790823.JavaMail.root@iiia.csic.es>
First Call for Papers for the Second Workshop on Semantic Deep Learning (Sem Deep -2) *** Deadline Monday 10 July 2017 for ALL submissions*** Scope: Based on the success of the first workshop on Semantic Deep Learning collocated with the European Semantic Web Conference (ESWC) 2017 , this second interdisciplinary workshop aims to bring together Semantic Web and Deep Learning practitioners. Deep Learning (DL) is a set of machine learning algorithms that acquire data features and representations by submitting data to possibly multi-layered neural networks. Semantic Web (SW) technologies focus on structuring data to form machine-readable conceptual models and knowledge resources. Both fields have considerably impacted data analysis and representation. We believe that the integration of SW technologies and resources with DL methods is very promising for the exploration of natural language semantics. We thus invite submissions that illustrate how Semantic Web technologies and resources can benefit from Deep Learning or build on Deep Learning results. At the same time, we are interested in submissions that show how Semantic Web technologies and resources can assist in DL tasks. Workshop Topics: Topics of interest for papers, posters, and software demonstrations of original and unpublished work include, but are not limited to: - semantic disambiguation with deep learning - neural networks and logic rules for semantic compositionality - learning semantic similarity and encoding distances as knowledge graph - deep learning semantic annotations - information retrieval and extraction with knowledge graphs and deep learning models - Deep Structured Semantic Models (DSSM) for the Semantic Web - multilingual semantic deep learning - learning and applying knowledge graph embeddings - reasoning with deep learning methods - deep learning models for ontology learning from text - predicting ontological relations with deep learning - deep learning Linked Data - ontology-based classification - learning semantic role labeling - investigation of compatibilities and incompatibilities between deep learning and Semantic Web approaches Submissions: Full papers: mature research work describing original research and its validation (6-8 pages, not including references) Short papers: research papers describing original research (3-4 pages, not including references) Project/demonstration notes: recent, ongoing or planned projects, early results and working demos (2-4 pages, including references) Please submit your paper by means of the easychair submission site of the ISA-13 workshop. For the formatting of submissions please follow the IWCS 2017 Formatting Instructions. Important dates: Paper submission deadline: 10 July 2017 - 23:59 Hawaii Time Notifications: 31 July 2017 Camera-ready version: 4 September 2017 Workshop: 19 September 2017 Location: Semantic Deep Learning is a workshop collocated with the 12th International Conference on Computational Semantics (IWCS) and will take place in Montpellier, France on 19 September 2017 . Organizing Committee: Georg Heigold, DFKI GmbH, Germany Dagmar Gromann, Artificial Intelligence Research Institute (IIIA - CSIC), Spain Thierry Declerck, Saarland University & DFKI GmbH, Germany Program Committee: Kemo Adrian, Artificial Intelligence Research Institute (IIIA-CSIC), Bellaterra, Spain Luis Espinosa Anke, Savana , Madrid, Spain Leon Derczynski, University of Sheffield, UK Stratos Kontopoulos, Multimedia Knowledge & Social Media Analytics Laboratory, Thessaloniki, Greece Brigitte Krenn, Austrian Research Institute for AI, Vienna, Austria Enrico Santus, The Hong Kong Polytechnic University, Hong Kong Felix Sasaki, W3C & DFKI GmbH, Berlin, Germany Vered Shwartz, Bar-Ilan University, Ramat Gan, Isreal Michael Spranger, Sony Computer Science Laboratories Inc., Tokyo, Japan Arkaitz Zubiaga, University of Warwick, Coventry, UK
Received on Wednesday, 10 May 2017 14:00:59 UTC