Abstract
Word Sense Disambiguation(WSD) is one of the traditionally most difficult problems in natural language processing and has broad theoretical and practical implications. One of the main difficulties for WSD systems is the lack of relevant knowledge–commonly known as the knowledge acquisition bottleneck problem. We present in this paper a novel method that utilizes dynamic Web data obtained through Web search engines to effectively enrich the semantic knowledge for WSD systems. We demonstrated through a word sense disambiguation system the large quantity and good quality of the extracted knowledge.
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Wang, Y., Hoffmann, A. (2006). Bootstrapping Word Sense Disambiguation Using Dynamic Web Knowledge. In: Yang, Q., Webb, G. (eds) PRICAI 2006: Trends in Artificial Intelligence. PRICAI 2006. Lecture Notes in Computer Science(), vol 4099. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-36668-3_151
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DOI: https://doi.org/10.1007/978-3-540-36668-3_151
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-36667-6
Online ISBN: 978-3-540-36668-3
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