Data Mining Mehmed Kantardzic (good english books to read .txt) 📖

Graphics Techniques for Scientific and Engineering Analysis, CRC Press, Boca Raton, 1995.

The book is a complete reference book on computer-graphic techniques for scientific and engineering visualization. It explains the basic methods applied in different fields to support an understanding of complex, volumetric, multidimensional, and time-dependent data. The practical computational aspects of visualization such as user interface, database architecture, and interaction with a model are also analyzed.

Spence, R., Information Visualization, Addison Wesley, Harlow, England, 2001.

This is the first fully integrated book on the emerging discipline of information visualization. Its emphasis is on real-world examples and applications of computer-generated interactive information visualization. The author also explains how these methods for visualizing information support rapid learning and accurate decision making.

Tufte, E. R., Beautiful Evidence, 2nd edition, Graphic Press, LLC, Cheshire, CT, 2007.

Beautiful Evidence is a masterpiece from a pioneer in the field of data visualization. It is not often an iconoclast comes along, trashes the old ways, and replaces them with an irresistible new interpretation. By teasing out the sublime from the seemingly mundane world of charts, graphs, and tables, Tufte has proven to a generation of graphic designers that great thinking begets great presentation. In Beautiful Evidence, his fourth work on analytical design, Tufte digs more deeply into art and science to reveal very old connections between truth and beauty—all the way from Galileo to Google.

APPENDIX A

This summary of some recognized journals, conferences, blog sites, data-mining tools, and data sets is being provided to help readers to communicate with other users of data-mining technology, and to receive information about trends and new applications in the field. It could be especially useful for students who are starting to work in data mining and trying to find appropriate information or solve current class-oriented tasks. This list is not intended to endorse any specific Web site, and the reader has to be aware that this is only a small sample of possible resources on the Internet.

A.1 DATA-MINING JOURNALS

1.Data Mining and Knowledge Discovery (DMKD)

http://www.kluweronline.com/issn/1384-5810/

DMKD is a premier technical publication in the Knowledge Discovery and Data Mining (KDD) field, providing a resource collecting common relevant 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 data mining and knowledge discovery surveys and tutorials of important areas and techniques, and detailed descriptions of significant applications. The scope of DMKD includes (1) theory and foundational issues including data and knowledge representation, uncertainty management, algorithmic complexity, and statistics over massive data sets; (2) data mining methods such as classification, clustering, probabilistic modeling, prediction and estimation, dependency analysis, search, and optimization; (3) algorithms for spatial, textual, and multimedia data mining, scalability to large databases, parallel and distributed data-mining techniques, and automated discovery agents; (4) knowledge discovery process including data preprocessing, evaluating, consolidating, and explaining discovered knowledge, data and knowledge visualization, and interactive data exploration and discovery; and (5) application issues such as application case studies, data-mining systems and tools, details of successes and failures of KDD, resource/knowledge discovery on the Web, and privacy and security.

2.IEEE Transactions on Knowledge and Data Engineering (TKDE)

http://www.computer.org/tkde/

The IEEE TKDE is an archival journal published monthly. The information published in this journal is designed to inform researchers, developers, managers, strategic planners, users, and others interested in state-of-the-art and state-of-the-practice activities in the knowledge and data-engineering area. We are interested in well-defined theoretical results and empirical studies that have potential impact on the acquisition, management, storage, and graceful degeneration of knowledge and data, as well as in provision of knowledge and data services. Specific topics include, but are not limited to, (1) artificial intelligence (AI) techniques, including speech, voice, graphics, images, and documents; (2) knowledge and data-engineering tools and techniques; (3) parallel and distributed processing; (4) real-time distributed; (5) system architectures, integration, and modeling; (6) database design, modeling, and management; (7) query design and implementation languages; (8) distributed database control; (9) algorithms for data and knowledge management; (10) performance evaluation of algorithms and systems; (11) data-communications aspects; (12) system applications and experience; (13) knowledge-based and expert systems; and (14) integrity, security, and fault tolerance.

3.Knowledge and Information Systems (KAIS)

http://www.cs.uvm.edu/∼kais/

KAIS is a peer-reviewed archival journal published by Springer. It provides an international forum for researchers and professionals to share their knowledge and report new advances on all topics related to knowledge systems and advanced information systems. The journal focuses on knowledge systems and advanced information systems, including their theoretical foundations, infrastructure, enabling technologies, and emerging applications. In addition to archival papers, the journal also publishes significant ongoing research in the form of short papers and very short papers on “visions and directions.”

4.IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)

http://computer.org/tpami/

IEEE TPAMI is a scholarly archival journal published monthly. Its editorial board strives to present most important research results in areas within TPAMI’s scope. This includes all traditional areas of computer vision and image understanding, all traditional areas of pattern analysis and recognition, and selected areas of machine intelligence. Areas such as machine learning, search techniques, document and handwriting analysis, medical-image analysis, video and image sequence analysis, content-based retrieval of image and video, face and gesture recognition, and relevant specialized hardware and/or software architectures are also covered.

5.Machine Learning

http://www.kluweronline.com/issn/0885-6125/

Machine Learning is an international forum for research on computational approaches to learning. The journal publishes articles reporting substantive results on a wide range of learning methods applied to a variety of learning problems. It features papers that describe research on problems and methods, applications research, and issues of research methodology as well as papers making claims about learning problems or methods provide solid support via empirical studies, theoretical analysis, or comparison to psychological phenomena. Application papers show the process of applying learning methods to solve important applications problems. Research methodology papers improve how machine-learning research is conducted. All papers describe the supporting evidence in ways that can be verified or replicated by other researchers. The papers also detail the learning component clearly and discuss assumptions regarding knowledge representation and the performance task.

6.Journal of Machine Learning Research