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22-466: GUIDO was first designed by Holger H. Hoos (then at Technische Universität Darmstadt , Germany , now at University of British Columbia , Canada ) and Keith Hamel ( University of British Columbia , Canada ). Later developments have been done by the SALIERI Project by Holger H. Hoos, Kai Renz and Jürgen F. Kilian. GUIDO Music Notation has been designed to represent music in a logical format (with

44-698: A high requirement to present and publish submitted papers. The focus is on innovative research in data mining, knowledge discovery, and large-scale data analytics. Papers emphasizing theoretical foundations are particularly encouraged, as are novel modeling and algorithmic approaches to specific data mining problems in scientific, business, medical, and engineering applications. Visionary papers on new and emerging topics are particularly welcomed. Authors are explicitly discouraged from submitting papers that contain only incremental results or that do not provide significant advances over existing approaches. In 2014, over 2,600 authors from at least fourteen countries submitted over

66-744: A part-time appointment as a professor of machine learning at Leiden University , and he is an adjunct professor at the Computer Science Department of the University of British Columbia , where he held a full-time professorial appointment from 2000 until 2016. His research interests are focused on artificial intelligence , at the intersection of machine learning , automated reasoning and optimization , with applications in empirical algorithmics , bioinformatics and operations research . In particular, he works on automated algorithm design and on stochastic local search algorithms . Since 2015, he

88-413: A thousand papers to the conference. A final 151 papers were accepted for presentation and publication, representing an acceptance rate of 14.6%. This acceptance rate is slightly lower than those of other top computer science conferences, which typically have a rate of 15–25%. The acceptance rate of a conference is only a proxy measure of its quality. For example, in the field of information retrieval,

110-643: Is a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) , and since 2020 a Fellow of the European Association for Artificial Intelligence (EurAI) as well as a Fellow of the Association for Computing Machinery (ACM). He wrote the book Stochastic Local Search: Foundations and Applications (with Thomas Stützle ), and his research is published widely in internationally leading journals and conference proceedings. In 2023 he received

132-408: Is extensively reviewed by multiple committee members and detailed feedback is given to each author. After review, decisions are made by the committee members to accept or reject the paper based on the paper’s novelty, technical quality, potential impact, clarity, and whether the experimental methods and results are clear, well executed, and repeatable. During the process, committee members also evaluate

154-593: Is limited to student authors only. "Best Student Paper Award" recognizes papers presented at the annual SIGKDD conference, with a student as a first author, that advance the fundamental understanding of the field of knowledge discovery in data and data mining. SIGKDD sponsors the KDD Cup data mining competition every year in conjunction with the annual conference. It is aimed at members of the industry and academia , particularly students, interested in KDD . SIGKDD has also published

176-543: Is recognized as a flagship venue in the field. Based on statistics provided by independent researcher Lexing Xie in her analysis “Visualizing Citation Patterns of Computer Science Conferences“ as part of the research in Computation Media Lab at Australian National University: The annual conference of ACM SIGKDD has received the highest rating A* from independent organization Computing Research and Education (a.k.a. CORE). Like all flagship conferences, SIGKDD imposes

198-539: Is similar to that of the LilyPond input format. Two obvious differences are the specification of octaves and durations, as shown in the example below. Both formats are to some extent inspired by the LaTeX format for typesetting text. Holger H. Hoos Holger H. Hoos is a German - Canadian computer scientist and a Alexander von Humboldt-professor of artificial intelligence at RWTH Aachen University . He also holds

220-586: The ACM SIGKDD test-of-time award for his work on Auto-WEKA , together with Chris Thornton, Frank Hutter and Kevin Leyton-Brown . He also works in computer music , where he created the SALIERI music programming language and computer music system (with Thomas Helbich, Jürgen Kilian and Kai Renz) as well as GUIDO music notation (with Keith Hamel). Hoos studied computer science at Department of Computer Science of

242-751: The Technische Universität Darmstadt and received his doctorate there in 1998. This biographical article relating to a Canadian computer specialist is a stub . You can help Misplaced Pages by expanding it . ACM SIGKDD SIGKDD , representing the Association for Computing Machinery 's (ACM) Special Interest Group (SIG) on Knowledge Discovery and Data Mining , hosts an influential annual conference. The KDD Conference grew from KDD (Knowledge Discovery and Data Mining) workshops at AAAI conferences, which were started by Gregory I. Piatetsky-Shapiro in 1989, 1991, and 1993, and Usama Fayyad in 1994. Conference papers of each proceedings of

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264-621: The WSDM conference has a lower acceptance rate than the higher-ranked SIGIR . The group recognizes members of the KDD community with its annual Innovation Award and Service Award. Each year KDD presents a Best Paper Award to recognizes papers presented at the annual SIGKDD conference that advance the fundamental understanding of the field of knowledge discovery in data and data mining. Two research paper awards are granted: Best Research Paper Award Recipients and Best Student Paper Award Recipients. Winning

286-598: The ACM SIGKDD Best Paper Award (Best Research Track Paper) is widely considered an internationally recognized significant achievement in a researcher's career. Authors compete with established professionals in the field, such as tenured professors, executives, and eminent industry experts from top institutions. It is common to find press articles and news announcements from the awardees’ institutions and professional media to celebrate this achievement. This award recognizes innovative scholarly articles that advance

308-510: The SIGKDD International Conference on Knowledge Discovery and Data Mining are published through ACM . KDD is widely considered the most influential forum for knowledge discovery and data mining research. The KDD conference has been held each year since 1995, and SIGKDD became an official ACM Special Interest Group in 1998. Past conference locations are listed on the KDD conference web site. The annual ACM SIGKDD conference

330-414: The ability to render to sheet music), whereas LilyPond is more narrowly focused on typesetting sheet music. GUIDO is not primarily focused on conventional music notation, but has been invented as an open format, capable of storing musical, structural, and notational information. GUIDO Music Notation is designed as a flexible and easily extensible open standard. In particular, its syntax does not restrict

352-488: The features it can represent. Thus, GUIDO can be easily adapted and customized to cover specialized musical concepts as might be required in the context of research projects in computational musicology. More importantly, GUIDO is designed in a way that when using such custom extensions, the resulting GUIDO data can still be processed by other applications that support GUIDO but are not aware of the custom extensions, which are gracefully ignored. This design also greatly facilitates

374-402: The field. This only difference between "Best Student Paper Award" and "Best Paper Award (Best Research Track Paper)" is the limitation in competition. All authors participating the conference are considered equally for "Best Paper Award (Best Research Track Paper)", and the award does not limit competition to any particular region, population, or age group. However, "Best Student Paper Award"

396-401: The fundamental understanding of the field of knowledge discovery in data and data mining. Each year, the award is given to authors of the strongest paper by this criterion, selected by a rigorous process. The selection process follows multiple rounds of peer reviews under stringent criteria. The selection committee consists of leading experts who provide insightful and independent analysis on

418-664: The incremental implementation of GUIDO support in music software, which can speed up the software development process significantly, especially for research software and prototypes. GUIDO has been split into three consecutive layers: Basic GUIDO introduces the main concepts of the GUIDO design and allows to represent much of the conventional music of today. Advanced GUIDO extends Basic GUIDO by adding exact score-formatting and some more advanced musical concepts. Finally, Extended GUIDO can represent user-defined extensions, like microtonal information or user defined pitch classes. Basic GUIDO notation

440-499: The merits and degree of innovation of the scholarly articles submitted by each author. The reviewers are required to be recognized subject experts who had extensive contributions to the specific subject area addressed by the paper. Reviewers are also required to be completely unaffiliated with the authors. First, all papers submitted to the ACM SIGKDD conference are reviewed by research track program committee members. Each submitted paper

462-402: The merits of each paper based on above factors, and make decision on recommending candidates for Best Paper Award (Best Research Track Paper). The candidates for Best Paper Award (Best Research Track Paper) are extensively reviewed by conference chairs and the best paper award committee. The final determination of the award is based on the level of advancement made by authors through the paper to

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484-565: The understanding of the field of knowledge discovery and data mining. Authors of a single paper who are judged to have contributed the highest level of advancement to the field are selected as recipients of this award. Anyone who submits a scholarly article to SIGKDD is considered for this award. The ACM SIGKDD Best Paper Award (Best Research Track Paper) was given to 49 individuals between 1997 and 2014. Among these individuals, most are distinguished persons and established professionals with celebrated careers, who have made significant contributions to

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