KESA 2017 - International Workshop on Knowledge Extraction and Semantic Annotation

KESA is a venue for presenting innovative systems and research results related the exploitation of formal models and procedures for knowledge extraction and semantic annotation.
In recent times, research groups have being dealing with various aspects in the area of computational linguistic, machine learning, stochastic and rule-based reasoning for processing knowledge. One of the critical step in this area is the linguistic processing phase, due to the fact that a significant amount of human knowledge can be found in texts.
KESA aims at bringing together researchers from various disciplines and industry interested in theories, methods and applications of knowledge extraction and management, data mining and semantic annotation, as well as in recent advances on data and knowledge bases.
The purpose of the workshop is to exchange new ideas and application experiences related to the development of knowledge and information management systems.
The chairs of Knowledge Extraction and Semantic Annotation are seeking original papers on research and development topics in the field of the topics listed below. Prospective authors are cordially invited to submit original technical papers up to 6 pages of length. Accepted papers will be published in the conference proceedings.
We solicit both academic, research, and industrial contributions. We welcome technical papers presenting research and practical results, position papers addressing the pros and cons of specific proposals, such as those being discussed in the standard fora or in industry consortia, survey papers addressing the key problems and solutions on any of the above topics short papers on work in progress, and panel proposals.
Industrial presentations are not subject to the format and content constraints of regular submissions. We expect short and long presentations that express industrial position and status.
Tutorials on specific related topics and panels on challenging areas are encouraged.
The topics suggested by the conference can be discussed in term of concepts, state of the art, research, standards, implementations, running experiments, applications, and industrial case studies. Authors are invited to submit complete unpublished papers, which are not under review in any other conference or journal in the following, but not limited to, topic areas.
All topics are open to both research and industry contributions
Shallow Parsing & Knowledge Extraction
Knowledge Discovery and Ontology Learning from unstructured sources
Knowledge Extraction based on (Linguistic) Linked Open Data
Data and text mining on (un)structured knowledge bases
Large-scale information extraction
Models for ontology engineering and resource integration
Tools in aid of NLP tasks and application
Machine learning for natural language
Semantic role labelling
Semantic search
Semantic Representation and Knowledge Acquisition
Cognitive, mathematical and computational models of language processing
Languages, methodologies and tools for representing and managing semantic annotations
Deep Language Processing
Linguistic and NLP Ontologies
Analysis of Ontology Models for Natural Language Texts