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Subject: CFP for IEEE Transactions on KDE Date: Monday 11 October 2004 15:18 From: Computational Science Announcements computational.science@optimanumerics.com To: computational.science@optimanumerics.com
Call for Papers
IEEE Transactions on Knowledge and Data Engineering----A Special Issue on
Intelligent Data Preparation
Data Preparation is the collection of algorithms and techniques that embodies data pre-processing in data analysis. It includes data integration, data transformation, noise detection, data cleaning/cleansing, data preprocessing, feature/attribute selection, information filtering, and data reduction. Data preparation enhances the useful information in the data by such as, resolving the inconsistency and conflicts, selecting relevant information, removing anomalies, correcting errors, filtering information, and clustering information and pattern reduction.
Many data analysis applications, such as data mining, Web mining, information retrieval, machine learning, and pattern recognition, require various forms of data preparation. In data preparation, one takes the data in their raw form, removes as much noise and redundancy as possible, and brings out the core that is ready for further processing. Indeed, data preparation often presents itself as a less glamorous but in fact more critical step than other steps in data analysis applications. It can be characterized as a data processing technique such that a minor data quality adjustment may potentially bring about much higher data mining effectiveness. However, in the past, much work in these relevant fields, such as data mining and machine learning, has been founded on quality data. The input to the data mining algorithms is assumed to conform to nice data distributions, containing no missing, inconsistent or incorrect values. This leaves a large gap between the available data and the available machinery to process the data.
This special issue will provide a forum for timely and in-depth presentation of progress in the theory and principles underlying data preparation.
Topics of Interest - Data Preparation Architectures - Data Preparation Foundations - Data Integration and Transformation - Noise Detection, Data Cleaning/Cleansing - Feature/Attribute Selection, Information Filtering, Data Reduction - Resolving Incompleteness, Inconsistency, and Conflicts of data - Removing Anomalies, Correcting Errors - Filling Missed Values, Reducing Ambiguity - Web Page Cleaning, Text Cleaning - Information/Data Clustering for data cleaning - Ontology Architectures for Data Mining
Submission Guidelines Please follow the guideline of the submissions on: http://www.computer.org/tkde/author_new.htm Important Dates Submission Deadline November 20, 2004 Author Notification April 8, 2005 Camera-ready Due April 28, 2005 Issue ships September 2005
Special Issue Guest Editors Prof. Chengqi Zhang (University of Technology, Sydney, Australia) Prof. Qiang Yang (Hong Kong University of Science and Technology, Hong Kong) Prof. Bing Liu (University of Illinois at Chicago, USA)
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