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» Unsupervised feature extraction using neuro-fuzzy approach
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SIGIR
2011
ACM
14 years 2 months ago
Pseudo test collections for learning web search ranking functions
Test collections are the primary drivers of progress in information retrieval. They provide a yardstick for assessing the effectiveness of ranking functions in an automatic, rapi...
Nima Asadi, Donald Metzler, Tamer Elsayed, Jimmy L...
EMNLP
2004
15 years 1 months ago
Trained Named Entity Recognition using Distributional Clusters
This work applies boosted wrapper induction (BWI), a machine learning algorithm for information extraction from semi-structured documents, to the problem of named entity recogniti...
Dayne Freitag
HAIS
2009
Springer
15 years 4 months ago
Unsupervised Feature Selection in High Dimensional Spaces and Uncertainty
Developing models and methods to manage data vagueness is a current effervescent research field. Some work has been done with supervised problems but unsupervised problems and unce...
José Ramón Villar, María del ...
ICASSP
2011
IEEE
14 years 3 months ago
Shout detection in noise
For the task of detecting shouted speech in a noisy environment, this paper introduces a system based on mel frequency cepstral coefficient (MFCC) feature extraction, unsupervise...
Jouni Pohjalainen, Paavo Alku, Tomi Kinnunen
AVSS
2007
IEEE
15 years 6 months ago
Vehicular traffic density estimation via statistical methods with automated state learning
This paper proposes a novel approach of combining an unsupervised clustering scheme called AutoClass with Hidden Markov Models (HMMs) to determine the traffic density state in a R...
Evan Tan, Jing Chen