Who publishes Data Mining and Knowledge Discovery?

Data Mining and Knowledge Discovery is published by Springer.

What is the ISSN of Data Mining and Knowledge Discovery?

The ISSN of Data Mining and Knowledge Discovery is 1384-5810.

What is the impact factor of Data Mining and Knowledge Discovery?

The reported impact factor of Data Mining and Knowledge Discovery is 4.3. Impact factor values are reproduced from publishers and may lag the latest JCR release.

What is the CCF ranking of Data Mining and Knowledge Discovery?

Data Mining and Knowledge Discovery is ranked CCF B in the China Computer Federation journal catalogue.

ジャーナル情報

Data Mining and Knowledge Discovery (DMKD)

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インパクトファクター:

4.3

出版社:

Springer

ISSN:

1384-5810

閲覧:

33860

フォロー:

58

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論文募集

Data Mining and Knowledge Discovery (DMKD) is an academic journal published by Springer. (ISSN 1384-5810, impact factor 4.3, CCF B).

Aims and scope Advances in data gathering, storage, and distribution have created a need for computational tools and techniques to aid in data analysis. Data Mining and Knowledge Discovery in Databases (KDD) is a rapidly growing area of research and application that builds on techniques and theories from many fields, including statistics, databases, pattern recognition and learning, data visualization, uncertainty modelling, data warehousing and OLAP, optimization, and high performance computing. KDD is concerned with issues of scalability, the multi-step knowledge discovery process for extracting useful patterns and models from raw data stores (including data cleaning and noise modelling), and issues of making discovered patterns understandable. Data Mining and Knowledge Discovery is the premier technical publication in the field, providing a resource collecting relevant common methods and techniques and a forum for unifying the diverse constituent research communities. The journal publishes original technical papers in both the research and practice of DMKD, surveys and tutorials of important areas and techniques, and detailed descriptions of significant applications. Short (2-4 pages) application summaries are published in a special section. The journal accepts paper submissions of any work relevant to DMKD. A summary of the scope of Data Mining and Knowledge Discovery includes: Theory and Foundational Issues: Data and knowledge representation; modelling of structured, textual, and multimedia data; uncertainty management; metrics of interestingness and utility of discovered knowledge; algorithmic complexity, efficiency, and scalability issues in data mining; statistics over massive data sets. Data Mining Methods: including classification, clustering, probabilistic modelling, prediction and estimation, dependency analysis, search, and optimization. Algorithms for data mining including spatial, textual, and multimedia data (e.g., the Web), scalability to large databases, parallel and distributed data mining techniques, and automated discovery agents. Knowledge Discovery Process: Data pre-processing for data mining, including data cleaning, selection, efficient sampling, and data reduction methods; evaluating, consolidating, and explaining discovered knowledge; data and knowledge visualization; interactive data exploration and discovery. Application Issues: Application case studies; data mining systems and tools; details of successes and failures of KDD; resource/knowledge discovery on the Web; privacy and security issues.

最終更新：Dou Sun（2026-01-04）

CCF	正式名称	インパクトファクター	出版社	ISSN
	Materials Discovery		Elsevier	2352-9245
	Social Network Analysis and Mining	2.8	Springer	1869-5450
	BioData Mining	6.1	Springer	1756-0381
	Journal of Big Data	6.4	Springer	2196-1115
	Scientific Data	6.9	Springer	2052-4463
B	ACM Transactions on Knowledge Discovery from Data	4.8	ACM	1556-4681
B	Software & Systems Modeling	3.2	Springer	1619-1366
B	Pattern Recognition	7.6	Elsevier	0031-3203
B	IEEE Transactions on Neural Networks and Learning Systems	8.9	IEEE	1045-9227
B	Information Sciences	6.0	Elsevier	0020-0255

CCF	ICORE	CP-I	略称	正式名称	投稿締切	開催日
		45.4	DMKD	International Conference on Data Mining and Knowledge Discovery	2024-04-08	2024-06-07
	B	65.1	Discovery Science	International Conference on Discovery Science	2026-06-15	2026-10-05
C	B	69.0	PAKDD	Pacific-Asia Conference on Knowledge Discovery and Data Mining	2025-11-15	2026-06-09
	C	53.3	IC3K	International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management	2026-07-03	2026-10-28
A	A*	96.4	KDD	ACM SIGKDD Conference on Knowledge Discovery and Data Mining	2026-07-19	2027-08-09
	B	63.8	DaWaK	International Conference on Big Data Analytics and Knowledge Discovery	2026-03-15	2026-08-11
		46.4	ICKD	International Conference on Knowledge Discovery	2020-08-05	2020-11-21
		37.9	KDML	International Conference on Knowledge Discovery and Machine Learning	2021-11-30	2021-12-22
B	A*	89.7	ICRA	International Conference on Robotics and Automation	2026-09-15	2027-05-24
B	A*	94.1	IJCAI	International Joint Conference on Artificial Intelligence	2026-01-31	2026-08-15

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Data Mining and Knowledge Discovery (DMKD)

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