Musicians make a standard: the MIDI phenomenon
Computer Music Journal
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Query by humming: musical information retrieval in an audio database
Proceedings of the third ACM international conference on Multimedia
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
Audio Feature Extraction and Analysis for Scene Segmentation and Classification
Journal of VLSI Signal Processing Systems - special issue on multimedia signal processing
Learning to Classify Text Using Support Vector Machines: Methods, Theory and Algorithms
Learning to Classify Text Using Support Vector Machines: Methods, Theory and Algorithms
Digital Coding of Waveforms: Principles and Applications to Speech and Video
Digital Coding of Waveforms: Principles and Applications to Speech and Video
Efficient Retrieval of Similar Time Sequences Under Time Warping
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Efficient Index Structures for String Databases
Proceedings of the 27th International Conference on Very Large Data Bases
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Manipulation, analysis and retrieval systems for audio signals
Manipulation, analysis and retrieval systems for audio signals
Learning drifting concepts: Example selection vs. example weighting
Intelligent Data Analysis
Evolutionary computation: comments on the history and current state
IEEE Transactions on Evolutionary Computation
Content-based audio classification and retrieval by support vector machines
IEEE Transactions on Neural Networks
GECCO '05 Proceedings of the 7th annual workshop on Genetic and evolutionary computation
Applications of knowledge discovery
IEA/AIE'2005 Proceedings of the 18th international conference on Innovations in Applied Artificial Intelligence
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
YALE: rapid prototyping for complex data mining tasks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Distributed feature extraction in a p2p setting: a case study
Future Generation Computer Systems - Special section: Data mining in grid computing environments
Aspect-Based Tagging for Collaborative Media Organization
From Web to Social Web: Discovering and Deploying User and Content Profiles
Optimization of Feature Processing Chain in Music Classification by Evolution Strategies
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Analytical features: a knowledge-based approach to audio feature generation
EURASIP Journal on Audio, Speech, and Music Processing
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Automatic index construction for multimedia digital libraries
Information Processing and Management: an International Journal
Similarity clustering of music files according to user preference
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
Multi-agent learning by distributed feature extraction
ALAMAS'05/ALAMAS'06/ALAMAS'07 Proceedings of the 5th , 6th and 7th European conference on Adaptive and learning agents and multi-agent systems: adaptation and multi-agent learning
Application challenges for ubiquitous knowledge discovery
Ubiquitous knowledge discovery
Nemoz: a distributed framework for collaborative media organization
Ubiquitous knowledge discovery
Application challenges for ubiquitous knowledge discovery
Ubiquitous knowledge discovery
Nemoz: a distributed framework for collaborative media organization
Ubiquitous knowledge discovery
Multi-objective feature selection in music genre and style recognition tasks
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Music genre classification using explicit semantic analysis
MIRUM '11 Proceedings of the 1st international ACM workshop on Music information retrieval with user-centered and multimodal strategies
Segment and combine approach for non-parametric time-series classification
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
Efficient case based feature construction
ECML'05 Proceedings of the 16th European conference on Machine Learning
An architecture for component-based design of representative-based clustering algorithms
Data & Knowledge Engineering
Feature selection for classification of oscillating time series
Expert Systems: The Journal of Knowledge Engineering
Assisted descriptor selection based on visual comparative data analysis
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
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Today, many private households as well as broadcasting or film companies own large collections of digital music plays. These are time series that differ from, e.g., weather reports or stocks market data. The task is normally that of classification, not prediction of the next value or recognizing a shape or motif. New methods for extracting features that allow to classify audio data have been developed. However, the development of appropriate feature extraction methods is a tedious effort, particularly because every new classification task requires tailoring the feature set anew.This paper presents a unifying framework for feature extraction from value series. Operators of this framework can be combined to feature extraction methods automatically, using a genetic programming approach. The construction of features is guided by the performance of the learning classifier which uses the features. Our approach to automatic feature extraction requires a balance between the completeness of the methods on one side and the tractability of searching for appropriate methods on the other side. In this paper, some theoretical considerations illustrate the trade-off. After the feature extraction, a second process learns a classifier from the transformed data. The practical use of the methods is shown by two types of experiments: classification of genres and classification according to user preferences.