CfP: Special issue on Semantic Resources and Text Mining


Call for Participation:
Semantic Resources and Text Mining
Frontiers in Research Metrics and Analytics, Text Mining and Literature-based Discovery

The scientific literature is increasingly characterised by a deluge of articles and the cross-disciplinary use of information. Hence, there is a dire need of effective tools to aid in monitoring and managing information contained within the literature. The development of text mining technologies is leading to profound changes in information management. The coupling of text mining methods and semantic resources is contributing to the emergence of new practices covering the entire life cycle of knowledge management, relating to how scientific knowledge, information and data are interpreted, described, disseminated, discovered, shared, and reused.

This themed issue aims to publish papers describing the coupling of semantic resources and text mining. We encourage submission of papers covering a broad range of methodological aspects, applications, and fundamental research.

We solicit article submissions covering the following topics:

  • Creating and updating semantic resources by mapping entities and relationships from text to semantic formal representations
  • Text annotation using semantic resources (e.g., OBIE, distant learning methods, transfer learning, weak supervision methods, zero/few shot learning). Definition and use of semantic distances.
  • Alignment or mapping between semantic resources using text corpus analysis.
  • Populating or curating databases and knowledge bases through text mining.
  • Entity linking or normalisation of multi-source data, using semantic resources for data integration. Making textual data more Findable, Accessible, Interoperable, and Reusable by using reference semantic resources (FAIR principles).
  • Creation of reference corpora with semantic annotations derived from semantic resources for training machine learning methods and for the evaluation of methods.
  • Evaluation framework. How semantic resources may be exploited to develop new criteria, measures, and practices in shared tasks.
  • Tools and workbenches for semantic annotation and for developing semantic resources. Platforms for creating NLP workflows.
  • Applications such as curation of information and ontology building for specific domains
  • User in the loop, including their role and cognitive processes in active learning, information curation, crowdsourcing, feedback providing or collaborative design of semantic resources. It may be related to Human-Machine Interfaces, explainability, interpretability and ethics.
  • Domain adaptation and transfer learning. Using semantic resources for the adaptation of text mining to new tasks and domains. Conversely, extending semantic resources by analysing various corpora.
  • Formal semantic representation, including philosophical considerations regarding the relationship between text corpora and formal semantic representation. Examples include formal representations capturing the meaning of words using corpus analysis, and the role of context in the meaning.

Topic Editors:

  • Claire Nédellec (French National Research Institute for Agriculture, Food and the Environment, France)
  • Sophia Ananiadou (The University of Manchester, National Centre for Text Mining, UK)
  • Fabio Rinaldi (Dalle Molle Institute for AI Research, Switzerland)

Submission Deadlines:

Abstract submission: 30th November 2020
Submission of full manuscripts: 28th February 2021

More information:

Abstract submission:
Guidelines for Authors:

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