الصفحة 1
الصفحة 1
Image and video retrieval ; Vol. 3568 ; 4th International conference, CIVR 2005, Singapore, July 20-22, 2005, Proceedings
It was our great pleasure to host the 4th International Conference on Image and Video Retrieval (CIVR) at the National University of Singapore on 20–22 July 2005. CIVR aims to provide an international forum for the discussion of research challenges and exchange of ideas among researchers and practitioners in image/video retrieval technologies. It addresses innovative research in the broad ?eld of image and video retrieval. A unique feature of this conference is the high level of participation by researchers from both academia and industry. Another unique feature of CIVR this year was in its format – it o?ered both the traditional oral presentation sessions, as well as the short presentation cum poster sessions. The latter provided an informal alternative forum for animated discussions and exchanges of ideas among the participants.After a rigorous review process, 20 papers were accepted for oral presentations, and 42 papers were accepted for poster presentations. In addition to the accepted submitted papers, the program also included 4 invited papers, 1 keynote industrial paper, and 4 invited industrial papers. Altogether, we o?ered a diverse and interesting program, addressing the current interests and future trends in this area.
Foundations of Intelligent Systems ; Vol. 3488 ; 15th International Symposium ISMIS 2005, Saratoga Springs, NY, USA, May 25-28, 2005, Proceedings
This volume contains the papers selected for presentation at the 15th International S- posiumonMethodologiesforIntelligentSystems, ISMIS2005, heldinSaratogaSprings, NewYork,25-28May,2005. ThesymposiumwasorganizedbySUNYatAlbany. Itwas sponsored by the Army Research Of?ce and by several units of the University at Albany including its Division for Research, College of Arts and Sciences, Department of C- puter Science, and Institute for Informatics, Logics, and Security Studies (formerly the Institute for Programming and Logics). The Program Committee selected the following major areas for ISMIS 2005: intelligent information systems, knowledge discovery and data mining, knowledge - formation and integration, knowledge representation, logic for arti?cial intelligence, soft computing, Web intelligence, Web services, and papers dealing with applications of intelligent systems in complex/novel domains. The contributed papers were selected from almost 200 full draft papers by the Program Committee members.
Foundations of Data Mining and Knowledge Discovery
This volume presents the results of investigations into the foundations of the discipline, and represents the state-of-the-art for much of the current research. This book will prove extremely valuable and fruitful for data mining researchers, no matter whether they would like to uncover the fundamental principles behind data mining, or apply the theories to practical applications.
Foundations and advances in data mining
In this carefully edited volume a theoretical foundation as well as important new directions for data-mining research are presented. It brings together a set of well respected data mining theoreticians and researchers with practical data mining experiences. The presented theories will give data mining practitioners a scientific perspective in data mining and thus provide more insight into their problems, and the provided new data mining topics can be expected to stimulate further research in these important directions.
Formal concept analysis ; Vol. 3403 ; 3rd International Conference, ICFCA 2005, Lens, France, February 14-18, 2005, Proceedings
This book constitutes a comprehensive and systematic presentation of the state of the art of formal concept analysis and its applications. The first part of the book is devoted to foundational and methodological topics. The contributions in the second part demonstrate how formal concept analysis is successfully used outside of mathematics, in linguistics, text retrieval, association rule mining, data analysis, and economics. The third part presents applications in software engineering.
Discovery science ; Vol. 3735 ; 8th International Conference, DS 2005, Singapore, October 8-11, 2005, Proceedings
This book constitutes the refereed proceedings of the 8th International Conference on Discovery Science, DS 2005, held in Singapore in October 2005, co-located with the International Conference on Algorithmic Learning Theory (ALT 2005). The 21 revised long papers and the 6 revised regular papers presented together with 9 project reports and 5 invited papers were carefully reviewed and selected from 112 submissions. The papers cover all issues in the area of automating scientific discovery or working on tools for supporting the human process of discovery in science.
Data Streams : Models and Algorithms
It primarily discusses issues related to the mining aspects of data streams rather than the database management aspect of streams. This volume covers mining aspects of data streams in a comprehensive style. Each contributed chapter, from a variety of well known researchers in the data mining field, contains a survey on the topic, the key ideas in the field from that particular topic, and future research directions.
Constraint-Based Mining and Inductive Databases ; European Workshop on Inductive Databases and Constraint Based Mining, Hinterzarten, Germany, March 11-13, 2004, Revised Selected Papers
The interconnected ideas of inductive databases and constraint-based mining are appealing and have the potential to radically change the theory and practice of data mining and knowledge discovery.
Machine learning for data streams : With practical examples in MOA
The book first offers a brief introduction to the topic, covering big data mining, basic methodologies for mining data streams, and a simple example of MOA. More detailed discussions follow, with chapters on sketching techniques, change, classification, ensemble methods, regression, clustering, and frequent pattern mining. Most of these chapters include exercises, an MOA-based lab session, or both. Finally, the book discusses the MOA software, covering the MOA graphical user interface, the command line, use of its API, and the development of new methods within MOA.
Machine Learning and Data Mining in Pattern Recognition ; 4th International Conference, MLDM 2005, Leipzig, Germany, July 9-11, 2005, Proceedings
Today, artificial intelligence deals with large amounts of data and knowledge and finds new information using machine learning and data mining. Machine learning and data mining are irreplaceable subjects and tools for the theory of pattern recognition and in applications of pattern recognition such as bioinformatics and data retrieval. This was the fourth edition of MLDM in Pattern Recognition which is the main event of Technical Committee 17 of the International Association for Pattern Recognition; it started out as a workshop and continued as a conference in 2003. Today, there are many international meetings which are titled “machine learning” and “data mining”, whose topics are text mining, knowledge discovery, and applications. This meeting from the first focused on aspects of machine learning and data mining in pattern recognition problems. We planned to reorganize classical and well-established pattern recognition paradigms from the viewpoints of machine learning and data mining. Though it was a challenging program in the late 1990s, the idea has inspired new starting points in pattern recognition and effects in other areas such as cognitive computer vision.
Local Pattern Detection ; International Seminar Dagstuhl Castle, Germany, April 12-16, 2004, Revised Selected Papers
Introduction The dramatic increase in available computer storage capacity over the last 10 years has led to the creation of very large databases of scienti?c and commercial information. The need to analyze these masses of data has led to the evolution of the new field knowledge discovery in databases (KDD) at the intersection of machine learning, statistics and database technology. Being interdisciplinary by nature, the field offers the opportunity to combine the expertise of different fields into a common objective. Moreover, within each field diverse methods have been developed and justified with respect to different quality criteria. We have to investigate how these methods can contributet o solving the problem of KDD. Traditionally, KDD was seeking to end global models for the data that - plain most of the instances of the database and describe the general structure of the data. Examples are statistical time series models, cluster models, logic programs with high coverageor classi?cation models like decision trees or linear decision functions. In practice, though, the use of these models often is very l- ited, because global models tend to end only the obvious patterns in the data, 1 which domain experts already are aware of . What is really of interest to the users are the local patterns that deviate from the already-known background knowledge. David Hand, who organized a workshop in 2002, proposed the new field of local patterns.
Knowledge Discovery in Inductive Databases ; Vol.3933 ; 4th International Workshop, KDID 2005, Porto, Portugal, October 3, 2005, Revised Selected and Invited Papers
The 4th International Workshop on Knowledge Discovery in Inductive Databases (KDID 2005) was held in Porto, Portugal, on October 3, 2005 in conjunction with the 16th European Conference on Machine Learning and the 9th European Conference on Principles and Practice of Knowledge Discovery in Databases. Ever since the start of the ?eld of data mining, it has been realized that the integration of the database technology into knowledge discovery processes was a crucial issue. This vision has been formalized into the inductive database perspective introduced by T. Imielinski and H. Mannila (CACM 1996, 39(11)). The main idea is to consider knowledge discovery as an extended querying p- cess for which relevant query languages are to be speci?ed.
Knowledge Discovery in Inductive Databases ; Vol.3377 : 3rd International Workshop, KDID 2004, Pisa, Italy, September 20, 2004, Revised Selected and Invited Papers
Cnstitutes the thoroughly refereed joint postproceedings of the Third International Workshop on Knowledge Discovery in Inductive Databases, KDID 2004, held in Pisa, Italy in September 2004 in association with ECML/PKDD. Inductive Databases support data mining and the knowledge discovery process in a natural way. In addition to usual data, an inductive database also contains inductive generalizations, like patterns and models extracted from the data. This book presents nine revised full papers selected from 23 submissions during two rounds of reviewing and improvement together with one invited paper. Various current topics in knowledge discovery and data mining in the framework of inductive databases are addressed.
Knowledge Discovery in Inductive Databases ; 5th International Workshop, KDID 2006 Berlin, Germany, September 18th, 2006 Revised Selected and Invited Papers
Constitutes the thoroughly refereed joint postproceedings of the 5th International Workshop on Knowledge Discovery in Inductive Databases, KDID 2006. The papers address various current topics in knowledge discovery and data mining in the framework of inductive databases such as constraint-based mining, database technology and inductive querying.
Knowledge discovery in databases : PKDD 2006 ; 10th European Conference on Principles and practice of knowledge discovery in databases, Berlin, Germany, September 18-22, 2006, Proceedings
The European Conference on Principles and Practice of Knowledge Discovery in Databases celebrates its tenth anniversary ; the first PKDD took place in 1997 in Trondheim, Norway. Over the years, the ECML/PKDD series has evolved into one of the largest and most selective international conferences in these areas, the only one that provides a common forum for the two closely related ?elds. In 2006, the 6th collocated ECML/PKDD took place during September 18-22, when the Humboldt-Universität zu Berlin hosted the 17th European Conference on Machine Learning (ECML) and the 10th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD). The successful model of a hierarchical reviewing process that was introduced last year for the ECML/PKDD 2005 in Porto has been taken over in 2006.
Knowledge Discovery in Databases : PKDD 2005 ; 9th European Conference on Principles and Practice of Knowledge Discovery in Databases, Porto, Portugal, October 3-7, 2005, Proceedings
585 different paper submissions were received for both events, which maintains the high s- mission standard of last year. Of these, 335 were submitted to ECML only, 220 to PKDD only and 30 to both. Such a high volume of scientific work required a tremendous effort from Area Chairs, Program Committee members and some additional reviewers. On average, PC members had 10 papers to evaluate, and Area Chairs had 25 papers to decide upon. We managed to have 3 highly qua- ?ed independent reviews per paper (with very few exceptions)and one additional overall input from one of the Area Chairs. After the authors’ responses and the online discussions for many of the papers, we arrived at the final selection of 40 regular papers for ECML and 35 for PKDD. Besides these, 32 others were accepted as short papers for ECML and 35 for PKDD. This represents a joint acceptance rate of around 13% for regular papers and 25% overall. We thank all involved for all the e?ort with reviewing and selection of papers. Besides the core technical program, ECML and PKDD had 6 invited speakers, 10 workshops, 8 tutorials and a Knowledge Discovery Challenge.
Advances in web mining and web usage analysis ; 8th International workshop on knowledge discovery on the web, WebKDD 2006 Philadelphia, USA, August 20, 2006 Revised Papers
The discipline of data mining delivers methodologies and tools for the an- ysis of large data volumes and the extraction of comprehensible and non-trivial insights from them. Web mining, a much younger discipline, concentrates on the analysisofdata pertinentto the Web.Web mining methods areappliedonusage data and Web site content; they strive to improve our understanding of how the Web is used, to enhance usability and to promote mutual satisfaction between e-business venues and their potential customers.Many ofthe infancy problems in Web mining have been solvedby now, but the tremendous potential for new and improved uses, as well as misuses, of the Web are leading to new challenges.
Advances in Data Mining : Theoretical aspects and applications ; 7th Industrial Conference, ICDM 2007, Leipzig, Germany, July 14-18, 2007, Proceedings
The book range from aspects of classification and prediction, clustering, Web mining, data mining in medicine, applications of data mining, time series and frequent pattern mining, and association rule mining.
Advanced data mining and applications ; Vol. 3584 ; 1st International Conference, ADMA 2005, Wuhan, China, July 22-24, 2005, Proceedings
This book constitutes the refereed proceedings of the First International Conference on Advanced Data Mining and Applications, ADMA 2005, held in Wuhan, China in July 2005. The 25 revised full papers and 75 revised short papers presented were carefully peer-reviewed and The papers are organized in topical sections on association rules, classification, clustering, novel algorithms, text mining, multimedia mining, sequential data mining and time series mining, web mining, biomedical mining, advanced applications, security and privacy issues, spatial data mining, and streaming data mining.
