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活动简介

第八届国际数据挖掘与大数据会议(DMBD'2023)是研究人员和从业者交流其在数据挖掘和大数据以及人工智能技术的理论、算法、模型和应用方面的进展和最新成果的国际性论坛。DMBD'2023是继广州、贝尔格莱德、清迈、上海、福冈、巴厘岛和北京之后的第八届活动,来自世界各地的数百名代表参加了这次活动,并展示了他们最新的成就、创新的想法、非凡的设计和卓越的实施。DMBD'2023将于2023年12月9日至12日在中国三亚举行。三亚位于海南岛最南端,被称为鹿城,也被称为“东方夏威夷”,是中国最南端的热带沿海旅游城市。它在中国四大一线旅游城市“三尾航厦”中排名第一,拥有岛上最美丽的海滨风景。
DMBD'2023正在征集数据挖掘与大数据及其应用方面的高质量原创研究论文。DMBD会议采用双盲审查方式审稿。我们希望今年在中国三亚举办一场高质量、令人激动的技术交流程序。在DMBD'2023上发表的论文将由中的Springer-Natured的计算机与信息科学(CCIS)通信出版(由EI、ISTP、DBLP、SCOPUS、ISI、Web of Science等编制索引)。我们DMBD会议论文集的下载量在Springer的所有出版物中位于前25%。某些高质量的论文将被推荐到SCI期刊(包括IEEE Trans,神经计算、具有应用的机器学习等)上发表。

本次会议由国际群体与进化智能学会主办,由北京大学、北京大数据研究院和南方的科技大学协办。其他支持机构有:IEEE计算智能学会、IEEE北京分会、世界软件联合会、国际神经网络学会、斯普林格-自然、CCIS等。

欢迎您在截稿日期(8月31日)之前向我们的DMBD'2023提交最新论文,我们将于今年12月在三亚欢迎您!

征稿信息

重要日期

2023-08-31
初稿截稿日期

Submission Guidelines
Prospective authors are invited to submit full-length papers (10-15 pages) to DMBD 2023 through the Online Paper Submission Systems, respectively, by the submission deadline. The submission of a paper implies that the paper is original and unpublished and will be presented by an author if accepted. Potential special track organizers are also invited to enlist five or more papers with cohesive topics to form special tracks.

All papers should be submitted electronically via Online Paper Submission Systems. The format of the initial submissions must be standard Springer CCIS style PDF. The files of the final accepted papers should be in either Word or Latex. Enquiries on paper submissions can be addressed to the secretariat at dmbd2023@iasei.org.

A complete paper should be submitted using the Springer CCIS template, which is blind-submission review-formatted template. The length should match that intended for final publication. Note that the DMBD 2023 reviewing is double blind, in that authors do not know the names of the reviewers of their papers, and reviewers do not know the names of the authors. Please read the Example Paper for detailed instructions on how to preserve anonymity. Avoid providing information that may identify the authors in the acknowledgments (e.g., co-workers and grant IDs) and in the supplemental material. Avoid providing links to websites that identify the authors.

All submitted papers will be refereed double-blindly by experts in the respective fields according to the criteria of originality, significance, quality, and clarity. The authors of accepted papers will have an opportunity to revise their papers and take consideration of the referees’ comments and suggestions, before submitting the final camera-ready version.

Papers presented at DMBD 2023 will be published in Springer Communications in Computer and Information Science (CCIS) (indexed by EI Compendex, ISI proceedings, ISTP, DBLP, etc.) and some high-quality papers will be selected for several SCI-indexed journals.

Paper Format
Papers must be single-spaced in one column format within an area of 122 mm x 193 mm with 10-point Times-Roman font. Each paper must exceed 10 pages and cannot exceed 15 pages including figures and references (papers beyond 15 pages are subject to page surcharge). All papers must be written in English using the Springer CCIS (Communications in Computer and Information Science) style, including all tables, figures, and references. It is required that the authors use the style file of Springer CCIS (template files for MS Word or LaTeX2e) when preparing the manuscripts to ensure the uniformity of papers.

For detials, please visit “Information for Authors of Computer Science Publications” on the website of Springer.

Presentation Modes
The presentation mode of a paper can be oral or poster depending on the preference of the authors and arrangement of the organizers. The authors can indicate their preferences on oral or poster presentation when submitting papers.

征稿范围

Data Mining

Classification and prediction
Clustering task
Case-Based,Similarity-Based reasoning
Mining text, semi-structured, spatio-temporal, streaming, graph, web, multimedia data
Systems for data mining
Machine learning
Reinforcement learning
Meta learning

Big Data

Data models and architectures
Deep learning architectures for handling big data
Privacy and security in big data analytics
Online and adaptive learning for big data streams
Data analytics and metrics
Tools and technologies QoS in big data
Large-scale text generation model
Large-scale generative adversarial network
Other large-scale model

FinTech

Quantitative investment
Intelligent investment strategy
Quantitative strategy
Quantization system
Market microstructure
Risk prediction
Credit modeling
Financial theories
Financial intelligent system
Financial Large-scale model

Applications

Techniques for Big Data Processing
Fraud detection and anomaly detection in large-scale datasets
Big data analytics for business intelligence
Smart city applications and urban analytics
Financial data analysis and stock market prediction
Recommender systems for online platforms and personalized recommendations
Network security
Intelligent diagnosis
Other applications

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重要日期
  • 会议日期

    12月09日

    2023

    12月12日

    2023

  • 08月31日 2023

    初稿截稿日期

主办单位
IEEE计算智能学会
IEEE北京分会
国际群体与进化智能学会
北京大学
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