An Adaptive Spell Checker Based on PS3M: Improving the Clusters of Replacement Words

Amorim, Renato Cordeiro de

doi:10.1007/978-3-540-93905-4_61

Search citation statements

Order By: Relevance

Paper Sections

Select...

Classification Via Clustering1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2012

2014

Publication Types

Select...

Article1

Book1

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

(1 citation statement)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Clustering is a widely used method [13][14][15][16][17][18] and K-means is probably its most well known algorithm. With it one can partition data into K non-overlapping clusters S={S 1 , S 2 ,…, S K } without the need of previous learning.…”

Section: Classification Via Clusteringmentioning

confidence: 99%

Anomalous pattern based clustering of mental tasks with subject independent learning – some preliminary results

Amorim

Mirkin²,

Gan³

2012

AIR

View full text Add to dashboard Cite

In this paper we describe a new method for EEG signal classification in which the classification of one subject's EEG signals is based on features learnt from another subject. This method applies to the power spectrum density data and assigns class-dependent information weights to individual features. The informative features appear to be rather similar among different subjects, thus supporting the view that there are subject independent general brain patterns for the same mental task.Classification is done via clustering using the intelligent k-means algorithm with the most informative features from a different subject. We experimentally compare our method with others.

show abstract