Data Mining Applied in Natural Language Processing

Dear Colleagues,

The objective of this Special Issue is to invite diverse submissions, fostering a collaborative initiative to comprehensively comprehend the emerging opportunities and challenges in the realm of data mining applied in natural language processing. We aim to identify key tasks, evaluate the current state of the art, showcase inventive methodologies and ideas, introduce substantial real-world systems or applications, propose new datasets, and engage in discussions about future directions. Through this coordinated effort, we aspire to advance our understanding of the intricate interplay between data mining and natural language processing, paving the way for advancements in the field.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but not limited to) the following areas (in alphabetical order):

• Computational Social Science and Social Media;
• Dialogue and Interactive Systems;
• Discourse and Pragmatics;
• Information Extraction;
• Interpretablity and Analysis of Models for NLP;
• Linguistic Theories, Cognitive Modeling, and Psycholinguistics;
• Machine Learning for NLP;
• Machine Translation and Multilinguality;
• Named Entity Recognition and Text Classification;
• Phonology, Morphology, and Word Segmentation;
• Semantics: Lexical, Sentence level, Textual Inference, and Other areas;
• Sentiment Analysis and Opinion Mining;
• Summarization;
• Syntax: Tagging, Chunking, and Parsing;
• Text Mining and Information Retrieval.

We look forward to receiving your contributions.

Technical Program Committee Member:

Dr. Yu Zhao  Southwestern University of Finance and Economic

Dr. Ruifan Li
Guest Editor

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