Advanced Natural Language Processing and Machine Translation
A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Processes".
Deadline for manuscript submissions: closed (25 November 2022) | Viewed by 18825
Special Issue Editor
Interests: information retrieval and text mining; interpretability and analysis of models for NLP; language model; machine learning for NLP; question answering; resources and evaluation; semantics and syntax parsing; speech and multimodality; text generation; machine translation systems and deployment; analysis of machine translation models and approaches; evaluation of machine translation quality; machine translation quality estimation; corpora and other resources for machine translation; natural language processing for machine translation
Special Issue Information
Dear Colleagues,
Natural language processing (NLP), also known as computational linguistics, is an interdisciplinary subject in computer science and linguistics. It is a branch of artificial intelligence involved in data mining, machine learning, knowledge acquisition, knowledge engineering, and linguistic research related to language computing. The difficulty of this field lies in the diversity, ambiguity, robustness, knowledge dependence, and context of language. The rise of natural language processing is closely related to machine translation (MT), which refers to the use of computers to automatically translate one language into another. This field is increasingly becoming a hot research topic due to its significant potential as a disruptive technology. It confronts various existing language barriers in innovative ways, striving to enable effective communication and translation across different languages by applying different approaches, technologies, and solutions. However, since NLP and MT systems depend on large data sets and computer power, numerous issues remain unsolved.
In this Special Issue, original and unpublished works presenting results in any way related to NLP or MT are welcome, especially those that include experimental and methodological novel solutions, system implementation approaches, new data sets and resources, natural language processing techniques and tools, hybrid solutions, technology combination and integration, incorporation of linguistic knowledge and other digital resources, translation quality evaluation and estimation, post-editing efforts and strategies, and other ways of tackling existing problems within the field of NLP. Nevertheless, submissions with a strong theoretical contribution are also encouraged.
Prof. Dr. Zhengtao Yu
Guest Editor
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Keywords
- topics of interest include, but are not limited to: information retrieval and text mining
- interpretability and analysis of models for NLP
- language model
- machine learning for NLP
- question answering
- resources and evaluation
- semantics and syntax parsing
- speech and multimodality
- text generation
- machine translation systems and deployment
- analysis of machine translation models and approaches
- evaluation of machine translation quality
- machine translation quality estimation
- corpora and other resources for machine translation
- natural language processing for machine translation
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