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NLDB 2017 : 22nd International Conference on Natural Language & Information Systems

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Conference Series : Applications of Natural Language to Data Bases
 
Link: http://conferences.hec.ulg.ac.be/~nldb2017/
 
When Jun 21, 2017 - Jun 23, 2017
Where University of Liège, Liège, Belgium
Abstract Registration Due Jan 22, 2017
Submission Deadline Feb 5, 2017
Notification Due Mar 13, 2017
Final Version Due Apr 3, 2017
Categories    NLP   machine learning   text mining   information retrieval
 

Call For Papers

***NLDB Conference Publications***

As a continuation of the NLDB tradition, all accepted papers will be published in the Lecture Notes in Computer Science (LNCS) series of Springer.

We are also planning a Special Issue in Data and Knowledge Engineering, an ISI-indexed, highly reputed journal of Elsevier. Authors of the best conference papers, to be selected at the end of the conference, will be invited to submit an extended version of the work to the journal.

Submission information can be found at the bottom of this page.

More information on NLDB 2017 can be found at http://conferences.hec.ulg.ac.be/~nldb2017/. (For an online version of this Call for Papers, please see http://conferences.hec.ulg.ac.be/~nldb2017/submissions/)

***Important Dates***

Abstract submission: January 29, 2017 (23h59 Hawaii Time)
Full paper submission: February 5, 2017 (23h59 Hawaii Time)
Paper notification: March 13, 2017 (23h59 Hawaii Time)
Camera-ready deadline: April 3, 2017 (23h59 Hawaii Time)

***NLDB 2017 at a glance***
NLDB 2017 invites researchers from academia and industry to submit their papers on recent, unpublished research that addresses theoretical aspects, algorithms and architectures of NLP applications in Information Systems (IS). Papers describing creation of resources, as well as survey and discussion papers, are also welcomed.

For its 22nd edition, we explicitly solicit submissions on recent advances in NLP, including trendsetting and relevant topics as neural language models and argumentation mining.
Specifically, we encourage submissions dealing with the following topics:

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, e.g., Toulmin model
- Argumentation mining from legal texts and scientific articles
- Applications, e.g., in opinion mining/sentiment analysis
- Neural Language Models

Deep Learning and Word2Vec
- Deep learning and 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

NLP Applications in IS and in Social Media and Web Analytics
- Machine translation
- 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

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)

Semantic Web, Open Linked Data, and Ontologies
- QALD
- Ontology learning and alignment
- Ontology population
- Ontology evaluation
- Querying ontologies and Linked Data
- Semantic tagging and classification
- Ontology-driven NLP

Natural Language in Conceptual Modeling
- Analysis of natural language descriptions
- Terminological ontologies
- Consistency checking
- Metadata creation and harvesting
- Ontology-driven systems integration
- Natural language and Ubiquitous Computing

Pervasive computing, embedded, robotic and mobile applications
- NLP techniques for Internet of Things (IoT)
- NLP techniques for ambient intelligence


Submission Information
All accepted papers will be included in Lecture Notes in Computer Science (LNCS) Springer proceedings of the conference, and, therefore, must comply with the LNCS format (http://www.springer.de/comp/lncs/authors.html).

Submitted papers can be of 4 types:
- Long papers (max. 12 pages, including references)
- Short papers (max. 6 pages, including references)
- Poster papers (max. 4 pages, including references)
- Demo papers (max. 4 pages, including references)
- Please note that the program committee may decide to accept some long papers as short papers or poster/demo papers, depending on the content quality. The same applies to short papers, which can be accepted as poster/demo contributions.

Manuscripts not submitted in the LNCS style or having more than the max. number of pages will not be reviewed and thus automatically rejected. The papers need to be original and not submitted or accepted for publication in any other workshop, conference, or journal.
Authors must submit their manuscripts (in PDF) via EasyChair (https://www.easychair.org/conferences/?conf=nldb2017). Submission via other means (e.g., emails) will be rejected.
Important: We plan to publish extended versions of a selection of the best papers after the conference in the Data & Knowledge Engineering journal as a special issue.

NLDB 2017 Program Chairs:
- Flavius Frasincar, Erasmus University Rotterdam, Rotterdam, the Netherlands
- Nguyen Le Minh, Japan Advanced Institute of Science and Technology, Japan
- Other members of the organization, including the Program Committee, can be found at http://conferences.hec.ulg.ac.be/~nldb2017/organization/

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