The contents of the latest issue of: International Journal of Data Warehousing and Mining (IJDWM) Official Publication of the Information Resources Management Association Volume 9, Issue 3, July – September 2013 Published: Quarterly in Print and Electronically ISSN: 1548-3924 EISSN: 1548-3932 Published by IGI Publishing, Hershey-New York, USA www.igi-global.com/ijdwm Editor-in-Chief: David Taniar, Monash University, Australia PAPER ONE Efficient Top-k Keyword Search Over Multidimensional Databases Ziqiang Yu (School of Computer Science and Technology, Shandong University, Jinan, China), Xiaohui Yu (School of Computer Science and Technology, Shandong University, Jinan, China & School of Information Technology, York University, Toronto, Canada) and Yang Liu (School of Computer Science and Technology, Shandong University, Jinan, China) Keyword search over databases has recently received significant attention. Many solutions and prototypes have been developed. However, due to large memory consumption requirements and unpredictable running time, most of them cannot be applied directly to the situations where memory is limited and quick response is required, such as when performing keyword search over multidimensional databases in mobile devices as part of the OLAP functionalities. In this paper, the authors attack the keyword search problem from a new perspective, and propose a cascading top-k keyword search algorithm, which generates supernodes by a branch and bound method in each step of search instead of computing the Steiner trees as done in many existing approaches. This new algorithm consumes less memory and significantly reduces the response time. Experiments show that the method can achieve high search efficiency compared with the state-of-the-art approaches. To obtain a copy of the entire article, click on the link below. http://www.igi-global.com/article/efficient-top-keyword-search-over/78373 To read a PDF sample of this article, click on the link below. http://www.igi-global.com/viewtitlesample.aspx?id=78373 PAPER TWO Modeling and Querying Continuous Fields with OLAP Cubes Leticia Irene Gómez (Instituto Tecnológico de Buenos Aires, Buenos Aires, Argentina), Silvia Alicia Gómez (Instituto Tecnológico de Buenos Aires, Buenos Aires, Argentina) and Alejandro Vaisman (Department of Computer & Decision Engineering (CoDE), Université Libre de Bruxelles, Brussels, Belgium) The notion of SOLAP (Spatial On-Line Analytical Processing) is aimed at exploring spatial data in the same way as OLAP operates over tables. SOLAP, however, only accounts for discrete spatial data. Current decision support systems are increasingly being needed for handling more complex types of data, like continuous fields, which describe physical phenomena that change continuously in time and/or space (e.g., temperature). Although many models have been proposed for adding spatial (continuous and discrete) information to OLAP tools, no one is general enough to allow users to just perceive data as a cube, and analyze any type of spatial data together with typical alphanumerical discrete OLAP data, using only the classic OLAP operators (e.g., Roll-up, Drill-down). In this paper the authors propose a model and an algebra supporting it, that allow operating over data cubes, independently of the underlying data types and physical data representation. That means, in this approach, the final user only sees the typical OLAP operators at the query level, whereas at lower abstraction levels the authors provide discrete and continuous spatial data support as well as different ways of partitioning the space. As far as the authors are aware of, this is the first proposal, which provides such a general framework for spatiotemporal data analysis. To obtain a copy of the entire article, click on the link below. http://www.igi-global.com/article/modeling-querying-continuous-fields-olap/78374 To read a PDF sample of this article, click on the link below. http://www.igi-global.com/viewtitlesample.aspx?id=78374 PAPER THREE A BPMN-Based Design and Maintenance Framework for ETL Processes Zineb El Akkaoui (Department of Computer & Decision Engineering (CoDE), Université Libre de Bruxelles, Brussels, Belgium), Esteban Zimányi (Department of Computer & Decision Engineering (CoDE), Université Libre de Bruxelles, Brussels, Belgium), Jose-Norberto Mazón (Department of Software and Computing Systems, University of Alicante, Alicante, Spain) and Juan Trujillo (Department of Software and Computing Systems, University of Alicante, Alicante, Spain) Business Intelligence (BI) applications require the design, implementation, and maintenance of processes that extract, transform, and load suitable data for analysis. The development of these processes (known as ETL) is an inherently complex problem that is typically costly and time consuming. In a previous work, the authors have proposed a vendor-independent language for reducing the design complexity due to disparate ETL languages tailored to specific design tools with steep learning curves. Nevertheless, the designer still faces two major issues during the development of ETL processes: (i) how to implement the designed processes in an executable language, and (ii) how to maintain the implementation when the organization data infrastructure evolves. In this paper, the authors propose a model-driven framework that provides automatic code generation capability and ameliorate maintenance support of our ETL language. They present a set of model-to-text transformations able to produce code for different ETL commercial tools as well as model-to-model transformations that automatically update the ETL models with the aim of supporting the maintenance of the generated code according to data source evolution. A demonstration using an example is conducted as an initial validation to show that the framework covering modeling, code generation and maintenance could be used in practice. To obtain a copy of the entire article, click on the link below. http://www.igi-global.com/article/bpmn-based-design-maintenance-framework/78375 To read a PDF sample of this article, click on the link below. http://www.igi-global.com/viewtitlesample.aspx?id=78375 ***************************************************** For full copies of the above articles, check for this issue of the International Journal of Data Warehousing and Mining (IJDWM) in your institution's library. This journal is also included in the IGI Global aggregated "InfoSci-Journals" database: http://www.igi-global.com/eresources/infosci-journals.aspx. ***************************************************** CALL FOR PAPERS Mission of IJDWM: The International Journal of Data Warehousing and Mining (IJDWM) aims to publish and disseminate knowledge on an international basis in the areas of data warehousing and data mining. It is published multiple times a year, with the purpose of providing a forum for state-of-the-art developments and research, as well as current innovative activities in data warehousing and mining. In contrast to other journals, this journal focuses on the integration between the fields of data warehousing and data mining, with emphasize on the applicability to real world problems. The journal is targeted at both academic researchers and practicing IT professionals. Coverage of IJDWM: The journal is devoted to the publications of high quality papers on theoretical developments and practical applications in data warehousing and data mining. Original research papers, state-of-the-art reviews, and technical notes are invited for publications. The journal accepts paper submission of any work relevant to data warehousing and data mining. Special attention will be given to papers focusing on mining of data from data warehouses; integration of databases, data warehousing, and data mining; and holistic approaches to mining and archiving data. A summary of the scope of data warehousing and mining includes: Data Warehousing: • Data mart • Data models • Data structures • Data warehousing process • Design • Online analytical process • Practical issues • Tools and languages Data Mining: • Algorithms • Applications issues • Data mining methods • Knowledge discovery process • Mining databases • Tools and languages IGI Global is pleased to offer a special Multi-Year Subscription Loyalty Program. In this program, customers who subscribe to one or more journals for a minimum of two years will qualify for secure subscription pricing. IGI Global pledges to cap their annual price increase at 5%, which guarantees that the subscription rates for these customers will not increase by more than 5% annually. Interested authors should consult the journal's manuscript submission guidelines www.igi-global.com/ijdwm. All data mining related papers that have been accepted for publication after 1-Jan-2012 will have their implementation source codes, executable programs, datasets, and user's manual be made available publicly in the IJDWM source code website at http://users.monash.edu/~dtaniar/IJDWM All inquiries and submissions should be sent to: Editor-in-Chief: David Taniar at David.Taniar@infotech.monash.edu.au