会議情報
MNLP 2020: IEEE Conference on Machine Learning and Natural Language Processing
http://www.ieee.ma/cist20/special-invited-sessions/nlp
提出日:
2020-07-19 Extended
通知日:
2020-09-21
会議日:
2020-12-12
場所:
Agadir - Essaouira, Morocco
年:
4
閲覧: 8342   追跡: 3   出席: 1

論文募集
The 4th IEEE Conference on "Machine Learning and Natural Language Processing: Models, Systems, Data and Applications" will be held within IEEE CiSt'20, the week of December 12th – 18th 2020, Agadir - Essaouira, Morocco.

The MNLP conference aims to explore and debate the latest technical status and recent innovations trends in the research and applications of natural language processing and machine learning models and technologies. The purpose of the conference is to provide an opportunity for the leading academic scientists, researchers, engineers, industrialists, scholars and other professionals from all over the world to interact and exchange their new ideas and research outcomes in related fields and develop possible chances for future collaboration. The conference is also aimed at motivating the next generation of researchers to promote their interests in machine learning and NLP.

NLP technologies and digital resources such as lexical databases, ontologies and corpora are instrumental to millions of people who use them every day without even being aware of them. Systems like Google Translate and web search engines rely more and more on levels of linguistic information automatically provided through NLP tools, and on huge repositories of structured language data. This development has deeply affected the way we think about language from a scientific perspective. Linguists have progressively turned their focus from abstract properties of language to the dynamics of its usage in communicative contexts. There is increasing awareness that language digital repositories, technologies and computational models of language processes not only shed considerable light on traditional issues in language and literary studies but may also lead to a radical reconceptualization of them. Aspects of language acquisition, lexical access, speech recognition, text translation, text analysis, ontology extraction, reading and optical character recognition can be put to a rigorous empirical test through computer simulations. Likewise, corpora, lexical databases and ontologies have helped us focus on the nature of language data from a different perspective. From this standpoint, digital data and computer technologies provide an empirical middle ground where interdisciplinary insights can be empirically assessed and integrated.

This conference is therefore equally intended to explore and debate the contribution of computational language models and language data to a better understanding of linguistic, psycholinguistic, sociolinguistic, historical and literary issues of the language and culture. We particularly welcome contributions addressing fundamental aspects of NLP, communication technology, language resources and automated text analysis by looking at their implications for both state-of-the-art language technologies and language knowledge at large.

TOPICS

We solicit submissions of original ideas and papers describing significant results and developments from both researchers and practitioners in a range of fields related but not limited to any of the following topics :

    Information retrieval and extraction
    Data, Web, and Text mining
    Named entity recognition
    Question answering
    Word sense disambiguation
    Machine Translation
    Stochastic language models
    Connectionist language models
    Language technologies for cultural heritage
    Optical character recognition
    Digital epigraphy
    Machine Learning models and applications
    Artificial Intelligence and Recommender systems
    Neural Networks
    Deep Learning
    Pattern Recognition
    Computer Vision
最終更新 Dou Sun 2020-07-19
関連会議
関連仕訳帳
CCF完全な名前インパクト ・ ファクター出版社ISSN
Information Security Technical ReportElsevier1363-4127
European Journal of Operational Research6.000Elsevier0377-2217
ROBOMECH Journal1.500Springer2197-4225
Journal of Optimization Theory and Applications1.600Springer0022-3239
IEEE Micro2.800IEEE0272-1732
Journal of Big Data8.600Springer2196-1115
International Journal of AnalysisHindawi2314-498X
Applied Ontology2.500IOS Press1570-5838
Complexity1.700Hindawi1076-2787
bJournal of Parallel and Distributed Computing3.400Elsevier0743-7315
完全な名前インパクト ・ ファクター出版社
Information Security Technical ReportElsevier
European Journal of Operational Research6.000Elsevier
ROBOMECH Journal1.500Springer
Journal of Optimization Theory and Applications1.600Springer
IEEE Micro2.800IEEE
Journal of Big Data8.600Springer
International Journal of AnalysisHindawi
Applied Ontology2.500IOS Press
Complexity1.700Hindawi
Journal of Parallel and Distributed Computing3.400Elsevier
おすすめ