Call for Papers - Data Mining & Warehousing

IMPORTANT DATES Deadline:    25th March 2012 Notification:    15th April 2012 Revision:        25th April 2012 Publication:    30th April 2012

International Journal of Research in Computer Science is now accepting manuscripts for its special issue on Data Mining and Warehousing. The intention of this issue is to present a collection of manuscripts that discuss and find out the modern trends, applications of Data Warehousing and Mining in computer science domain. Prime Focus is to emphasize upon the core problems/issues that occur in the data storage and management world. These problems strengthen even more when data is large and complex in structure. Submission: Only original research papers will be considered. Authors are requested to submit their papers through the submission form available at: www.ijorcs.org/submit-paper Note: Do not forget to mention "Data Mining and Warehousing" in the additional comments box in the form. Review and Publication process: After submission of the manuscript, the author will be informed by the editorial team about its acceptance as soon as possible. Meanwhile an author can track status of the manuscript via a 'Track Box' located at our homepage, www.ijorcs.org. After acceptance and confirmation of fees, paper will be published in our upcoming issue.

Topic Coverage

This issue covers the following topics under data mining and warehousing, but authors are not limited only to these topics. Any other topic falling in this domain is acceptable.

• Complex data description languages and formats
• Complex data integration
• Complex data warehouse foundations, design and architectures
• Data Exchange, Integration, quality, cleaning and Lineage
• XML data warehousing
• Complex data warehouse consistency and quality
• Database Monitoring and Tuning
• Multidimensional modeling of complex data
• OLAP on complex data
• Mining different data formats
• Data Privacy and Security
• Combining mining results from different sources
• Mining data streams
• Data Mining and neural network
• Combining OLAP and data mining for complex data analysis
• Metadata, Multilingual and Multimedia Data Management
• Human-machine interfaces for complex data mining
• Management of metadata and domain-related knowledge
• Query Processing and Optimization
• Interoperability and heterogeneity
• Exploiting metadata or domain-related knowledge in the analysis process
• Text Search and Database Querying
• .......................And many more.....................