Large-Scale Data Mining and Decision Automation
A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Systems".
Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 651
Special Issue Editors
Interests: data mining; operations management; supply chain analytics; social commerce
Interests: algorithmic data science; mining data of combinatorial structures; data-driven operations management
Special Issue Information
Dear Colleagues,
In the era of artificial intelligence, the rise of big data technology appears to have empowered AI with rich information that provides an unprecedented opportunity for decision automation. Big data is now available in different areas. For example, we have GPS data for human mobility analysis, social media data for user engagement and marketing analysis, and supply chain data for operations management. While tremendous effort has been made to extract useful information from big data, it is desired to understand how various data mining and optimization algorithms can benefit the development of intelligent systems for decision automation. Most likely, the growth of data mining and optimization for large-scale decision automation will accelerate in the upcoming years. For example, we can further analyze GPS data for ride-sharing scheduling, utilize social media data for personalized marketing campaigns, and aggregate supply chain data for intelligent ordering and replenishment systems. Despite the many benefits of big data mining, it creates new challenges in solving these large-scale problems. The big data comes from multiple sources and is collected with noisy and sparse records. The optimization relies on accurate parameter inputs, and becomes intractable when solving large-scale problems. This Special Issue aims to publish papers furthering the utilization of big data for large-scale data mining and optimization that facilitate the development of decision automation systems. We encourage innovative business models and novel use cases that can benefit large-scale data mining or optimization. Possible topics include, but are not limited to, the following:
- Large-scale data mining and knowledge discovery;
- Large-scale optimization;
- Social media analytics;
- Data-driven approaches;
- Decision automation strategies;
- Stochastic, online, and robust algorithms;
- Adaptive learning;
- Data-driven digital platforms;
- Human mobility analytics.
Dr. Junming Liu
Dr. Yu Yang
Dr. Jingyuan Yang
Guest Editors
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 100 words) can be sent to the Editorial Office for announcement on this website.
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.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- data mining
- decision automation
- large-scale optimization
- information retrieval
- operations management
- decision support systems
- user behavior analysis
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.
Further information on MDPI's Special Issue policies can be found here.
