European Conference on Natural Language Processing and Information Retrieval (ECNLPIR)

Description

The European Conference on Natural Language Processing and Information Retrieval (ECNLPIR) covers topics such as:

  • Applications of SW and NLP for digital humanities, intelligent tutoring, social sciences
  • Adversarial and cross language information retrieval
  • Author identification and plagiarism detection
  • Aspects of high performance text analysis
  • Collaborative information filtering
  • Automated knowledge aquisition and representation
  • Data mining and knowledge discovery from Linked Data and ontologies
  • Combining NL and SW in learning environments
  • Decentralised knowledge representation, search and IR
  • Data, information and knowledge integration across languages
  • Dialogue systems for the SW
  • Diachronic corpora and temporal reasoning over knowledge basis
  • Event and anomaly detection - Sentiment analysis
  • Document summerisation and identification
  • Graph- and deep-learning-based methods of NLP and IR
  • Fundamentals of data scienec, data & text mining, interactive systems, information mining and psycholinguistic
  • Interactive, dynamic as well as contextual and personalised IR
  • Information and knowledge extraction (including taxonomy extraction, ontology learning, knowledge graph learning)
  • Language resources, corpora building and annotation languages for the SW
  • IR result evaluation and relevance feedback
  • Learning from Big Data for web-scale knowledge graphs
  • Learning Analytics Knowledge
  • Methods and analyses for statistical networks, small world graphs, dynamic graphs and in particular co-occurrence graphs
  • Lexical semantics for the SW
  • Methods based on Swarm Intelligence and other natural inspired methods
  • Methods and systems of automatic machine translation
  • Multimodal human-computer communication for the SW
  • Methods for Classification and Categorisation
  • Natural language understanding
  • Natural language text generation from knowledge graphs and ontologies
  • NL-based representations and knowledge systems using SW languages
  • Natural language understanding and the SW
  • Ontology generation, merging and verification methods
  • Ontologies, knowledge representation, semantic web technologies
  • Opinion, personality and emotion detection in social media
  • Ontology population through NLP and IR methods
  • Query Expansion
  • Propagation and diffusion of information, super popular content
  • Resources for basic NLP tasks (word segmentation, tagging, stemming, parsing and syntactical analysis, corpus-based language engineering, named entity recognition, syntactic analysis, semantic analysis, discourse analysis, speech recognition, speech synthesis, etc.)
  • Question answering over knowledge graphs
  • Semantic search and exploratory search
  • Self-organisation and –maintenance of information in the WWW
  • Similarity analysis, clustering, hierarchic clustering
  • Semantic similarity metrics and analogy
  • Text analytics for the Internet of Things
  • Social and multimedia IR
  • Use of knowledge graphs and ontologies for NLP
  • Topic recognition and topic tracking, subject indexing
  • Visualisation of NLP and IR results

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