Computer Science – Computation and Language
Scientific paper
2008-10-07
ECAI 2006: 17th European Conference on Artificial Intelligence. Riva del Garda, Italy, 29 August - 1st September 2006
Computer Science
Computation and Language
6 pages, 7 embedded figures, LaTeX 2e using the ecai2006.cls document class and the algorithm2e.sty style file (+ standard pac
Scientific paper
Without prior knowledge, distinguishing different languages may be a hard task, especially when their borders are permeable. We develop an extension of spectral clustering -- a powerful unsupervised classification toolbox -- that is shown to resolve accurately the task of soft language distinction. At the heart of our approach, we replace the usual hard membership assignment of spectral clustering by a soft, probabilistic assignment, which also presents the advantage to bypass a well-known complexity bottleneck of the method. Furthermore, our approach relies on a novel, convenient construction of a Markov chain out of a corpus. Extensive experiments with a readily available system clearly display the potential of the method, which brings a visually appealing soft distinction of languages that may define altogether a whole corpus.
Henry Claudia
Nielsen Frank
Nock Richard
Vaillant Pascal
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