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2010

Multi-label ASRS Dataset Classification Using Semi Supervised Subspace Clustering

10 years 2 months ago
Multi-label ASRS Dataset Classification Using Semi Supervised Subspace Clustering
There has been a lot of research targeting text classification. Many of them focus on a particular characteristic of text data - multi-labelity. This arises due to the fact that a document may be associated with multiple classes at the same time. The consequence of such a characteristic is the low performance of traditional binary or multi-class classification techniques on multi-label text data. In this paper, we propose a text classification technique that considers this characteristic and provides very good performance. Our multi-label text classification approach is an extension of our previously formulated [3] multi-class text classification approach called SISC (Semi-supervised Impurity based Subspace Clustering). We call this new classification model as SISC-ML(SISC Multi-Label). Empirical evaluation on real world multi-label NASA ASRS (Aviation Safety Reporting System) data set reveals that our approach outperforms state-of-theart text classification as well as subspace cluster...
Mohammad Salim Ahmed, Latifur Khan, Nikunj C. Oza,
Added 10 Feb 2011
Updated 10 Feb 2011
Type Journal
Year 2010
Where CIDU
Authors Mohammad Salim Ahmed, Latifur Khan, Nikunj C. Oza, Mandava Rajeswari
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