期刊名称：DATA MINING AND KNOWLEDGE DISCOVERY
 期刊简介(About the journal)
投稿须知(Instructions to Authors)
编辑部信息(Editorial Board)
About the journal
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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 intended to be 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¨C4 pages) application summaries are published in a special section.
The journal accepts paper submissions of any work relevant to DMKD. A detailed call for papers is provided on-line at http://www.microsoft.com/research/datamine. 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 distributred 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 explaing 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. |
Instructions to Authors
Authors are encouraged to submit high quality, original work that has not appeared in, nor is under consideration by, other journals. Papers, which have previously appeared in conference proceedings, will be considered, and this should be so indicated at the time of submission.
ONLINE MANUSCRIPT SUBMISSION
Kluwer Academic Publishers now offers authors, editors and reviewers of Data Mining and Knowledge Discovery the use of our fully web-enabled online manuscript submission and review system. To keep the review time as short as possible, we request authors to submit manuscripts online to the journal¡®s editorial office. Our online manuscript submission and review system offers authors the option to track the progress of the review process of manuscripts in real time. Manuscripts should be submitted to:
http://DAMI.edmgr.com
The online manuscript submission and review system for Data Mining and Knowledge Discovery offers easy and straightforward log-in and submission procedures. This system supports a wide range of submission file formats, including: for manuscripts - Word, WordPerfect, RTF, TXT, and LaTex; for figures, TIFF, GIF, JPEG, EPS, PPT and Postscript. PDF is not an acceptable format.
NOTE: In case you encounter any difficulties while submitting your manuscript online, please get in touch with the responsible Editorial Assistant by clicking on "CONTACT US" from the tool bar.
Authors should send a completed and duly signed Consent to Publish and Transfer of Copyright form (to be downloaded from the journal's homepage) either by mail or fax to the Editorial Office of Data Mining and Knowledge Discovery. Authors should still follow the regular instructions for authors when preparing their manuscripts (see below).
Michelle Misner
DAMI - Editorial Office
Kluwer Academic Publishers
101 Philip Drive
Assinippi Park
Norwell, MA 02061, USA
Telephone: (781)681-0613
Fax: (781)878-0449
E-mail: Michelle.Misner@wkap.com
Manuscript Style
- Use an informative title for the paper and include an abstract of 100 to 250 words at the head of the manuscript. The abstract should be a carefully worded description of the problem addressed, the key ideas introduced, and the results. Abstracts will be printed with the article.
- Provide from 3 to 5 keywords.
- Provide a list of all footnotes, beginning with Affiliation of author and continuing with numbered footnotes. Acknowledgment of financial support may be given if appropriate.
- References should appear in a separate bibliography at the end of the paper in alphabetical order with items referred to in the text by author and date of publication in parentheses, e.g., (Marr, 1992). References should be complete, in the following style:
Style for papers:
Authors, last names followed by first initials, year of publication, title, volume, inclusive page numbers.
Style for books:
Authors, year of publication, title, publisher and location, chapter and page numbers (if desired).
Examples as follows:
- (Book) Marr, D. 1982. Vision, A Computational Investigation into the Humanreak Representation & Processing of Visual Information. San Francisco: Freeman.
- (Journal) Rosenfeld, A. and Thurston, M. 1971. Edge and curve detection for visual scene analysis. IEEE Trans. Comput., C 20:562-569.
- (Conference Proceedings) Witkin, A. 1983. Scales space filtering. Proc. Int. Joint Conf. Artif. Intell. Karlsruhe, West Germany, pp.1019-1021.
- (Lab. memo.) Yuille, A.L. and Poggio, T. Scaling theorems for zero crossings. M.I.T. Artif. Intel. Lab., Massachusetts Inst. Technol., Cambridge, MA, A.I. Memo. 722.
- Type mathematical expressions exactly as they should appear in print. Use appropriate typeface. It will be assumed that letters in displayed equations are to be set in italic type unless noted otherwise. All letter symbols in text discussion should be italic or boldface. Indicate best breaks for equations in case they will not fit on one line.
Illustration Style
- Illustrations should be sharp, noise-free, and of good contrast. We regret that we cannot provide drafting or art service.
- Each figure should be mentioned in the text and numbered consecutively using Arabic numerals. Specify the desired location of each figure in the text. Each figure must have a caption. Proper style for captions, e.g., Fig.3. Examples of the fault coverage of random vectors in (a)combinational and (b)sequential circuits.
- Number each table consecutively using Arabic numerals. Please label any material that can be typeset as a table, reserving the term figure for material that has been drawn. Specify the desired location of each table in the text. Type a brief title above each table.
- All lettering should be large enough to permit legible reduction.
Proofing
Please be sure to include your e-mail address on your paper. If your paper is accepted, we will be forwarding your page proofs via e-mail. Your cooperation is appreciated. The proofread copy should be received back by the Publisher within 72 hours.
Copyright
It is the policy of Kluwer Academic Publishers to own the copyright of all contributions it publishes. To comply with the U.S. Copyright Law, authors are required to sign a copyright transfer form before publication. This form returns to authors and their employers full rights to reuse their material for their own purposes. Authors must submit a signed copy of this form with their manuscript.
Reprints
Each group of authors will be entitled to 50 free reprints of their paper.
Editorial Board
Editor-in-Chief:
Usama Fayyad
digiMine, Inc., Kirkland, WA, USA
Heikki Mannila
Helsinki University of Technology, Finland
Raghu Ramakrishnan
Computer Science Dept., University of Wisconsin, Madison, USA
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