Abstract
Phonetic string search of written text is an important topic in Information Retrieval (IR). A major difficulty is the inconsistencies between relevance judgements, which makes it possible for a successful method to fail with a new dataset. This paper discusses an adaptive model based on the novel syllable alignment pattern searching algorithm. Experimental results show that it is convenient and effective to be trained for different datasets.
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© 2005 Springer-Verlag Berlin Heidelberg
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Ruibin, G., Yun, C.K. (2005). An Adaptive Model for Phonetic String Search. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3683. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11553939_129
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DOI: https://doi.org/10.1007/11553939_129
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28896-1
Online ISBN: 978-3-540-31990-0
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