23rd International Conference on Natural Language & Information Systems NLDB 2018

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活动简介

Since 1995, the NLDB conference brings together researchers, industry practitioners, and potential users interested in various application of Natural Language in the Database and Information Systems field.

The term 'Information Systems" has to be considered in the broader sense of Information and Communication Systems, including Big Data, Linked Data and Social Networks.

The field of Natural Language Processing (NLP) has itself recently experienced several exciting developments. In research, these developments have been reflected in the emergence of neural language models (Deep Learning, Word2Vec) and a (renewed) interest in various linguistic phenomena, such as in discourse and argumentation theory (argumentation mining). Regarding applications, NLP systems have evolved to the point that they now offer real-life, tangible benefits to enterprises. Many of these NLP systems are now considered a de-facto offering in business intelligence suites, such as algorithms for recommender systems and opinion mining/sentiment analysis as well as question-answering systems.

It is against this backdrop of recent innovations in NLP and its applications in information systems that the 23rd edition of the NLDB conference – NLDB2018, takes place. We welcome research and industrial contributions, describing novel, previously unpublished works on NLP and its applications across a plethora of topics as described in the Call for Papers.

NLDB 2018 is organized in Paris (France), from the 13rd-15th June 2018.

征稿信息

重要日期

2018-02-05

初稿截稿日期

2018-03-20

初稿录用日期

2018-04-03

终稿截稿日期

征稿范围

Topics of interest include but are not limited to:

Argumentation Mining and Applications: Automatic detection of argumentation components and relationships, Creation of resources, e.g. annotated corpora, treebanks and parsers, Integration of NLP techniques with formal, Abstract argumentation structures, Argumentation Mining from legal texts and scientific articles, Applications, e.g. in opinion mining/sentiment analysis
Deep Learning, Neural Languages and NLP: Word2Vec applications, e.g. opinion mining, text summarization, machine translation, Development of novel deep learning architectures and algorithms, Parallel computation techniques and GPU programming for neural language models
Social Media and Web Analytics: Plagiarism detection, Opinion mining/sentiment analysis, detection of fake reviews, Information extraction: NER, event detection, term and semantic relationship extraction, Text summarization, Text classification and clustering, Corpus analysis, Language detection, Robust NLP methods for sparse, ill-formed texts, Recommendation systems
Question Answering (QA): Natural language interfaces to databases, QA using web data, Multi-lingual QA, Non-factoid QA(how/why/opinion questions, lists), Geographical QA, QA corpora and training sets, QA over Linked Data (QALD)
Corpus Analysis: Multi-lingual and Multi-cultural corpus, Machine translation, Text analysis, Classification systems, Extraction, Named Entity and Event Extraction
Semantic Web, Open Linked Data, and Ontologies: Ontology learning and alignment, Ontology population, Ontology evaluation, Querying ontologies and Linked Data, Semantic tagging and classification, Ontology-driven NLP, Ontology-driven systems integration
Natural Language in Conceptual Modeling: Analysis of natural language descriptions, NLP in requirement Engineering, Terminological ontologies, Consistency checking, Metadata creation and harvesting
Natural language and Ubiquitous Computing: Pervasive computing, embedded, robotic and mobile applications, NLP techniques for Internet of Things (IoT), NLP techniques for ambient intelligence
Big Data and Business intelligence: Identity Detection, Semantic Data cleaning, Summarisation, Reporting.