Abstract
We propose a framework for constructing semantic features for textual documents from tackling the problem of abstracting information in document representation. Semantic patterns are discovered from ontology-derived texts which provide rich contextual information regarding the concepts. The patterns represent the syntactic and semantic relationships implied in the textual documents which can help in extracting and representing the underlying concepts in texts. We also investigate the significance of using the patterns in automatic summarization of biomedical articles.
The work described in this paper was substantially supported by grants from the Research Grant Council of the Hong Kong Special Administrative Region, China (Project Nos: CUHK 4179/03E and CUHK 4193/04E) and CUHK Strategic Grant (No: 4410001).
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Chan, K., Lam, W. (2005). Discovering Patterns from Ontology-Derived Texts. In: Fox, E.A., Neuhold, E.J., Premsmit, P., Wuwongse, V. (eds) Digital Libraries: Implementing Strategies and Sharing Experiences. ICADL 2005. Lecture Notes in Computer Science, vol 3815. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11599517_47
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DOI: https://doi.org/10.1007/11599517_47
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