Data Modeling and Predictive Analytics

Dear Colleagues,

Data modeling is carried out to improve the quality of data, which eventually helps processes to identify interesting patterns and carry out predictions. Many of the latest research and development trends suggest and attempt to build data modeling, cleansing, and preparation techniques that are aligned towards improving and enhancing the performance and effectiveness of analysis and prediction mechanisms. This requires advanced methods, techniques, and tools that perform modeling, representation, and preparation of data in alignment with reasoning, analytics, and prediction.

The purpose of this Special Issue is to present the latest research in data modeling, predictive analytics, and related areas. Researchers and practitioners in these areas are invited to submit their original unpublished research works.

Topics of interest include but are not limited to:

• Data modeling
• Knowledge representation
• Reasoning
• Data preprocessing and transformation
• Feature engineering
• Predictive analytics
• Ontologies and metadata
• Knowledge graphs
• Complex event modeling and processing
• Cataloguing and organization
• Semantic web and rules
• Natural language modeling and processing
• Rule-driven and data-driven reasoning
• Prediction and forecasting
• Machine learning
• Deep learning

Dr. M. Omair Shafiq
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.

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