Abstract
Document-category integration (or category integration for short) is fundamental to many e-commerce applications, including information integration along supply chains and information aggregation by intermediaries. Because of the trend of globalization, the requirement for category integration has been extended from monolingual to poly-lingual settings. Poly-lingual category integration (PLCI) aims to integrate two document catalogs, each of which consists of documents written in a mix of languages. Several category integration techniques have been proposed in the literature, but these techniques focus only on monolingual category integration rather than PLCI. In this study, we propose a feature-reinforcement-based PLCI (namely, FR-PLCI) technique that takes into account the master documents of all languages when integrating source documents (in the source catalog) written in a specific language into the master catalog. Using the monolingual category integration (MnCI) technique as a performance benchmark, our empirical evaluation results show that our proposed FR-PLCI technique achieves better integration accuracy than MnCI does in both English and Chinese category integration tasks.
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Wei, CP., Chen, CC., Cheng, TH., Yang, C.C. (2009). A Feature-Reinforcement–Based Approach for Supporting Poly-Lingual Category Integration. In: Weinhardt, C., Luckner, S., Stößer, J. (eds) Designing E-Business Systems. Markets, Services, and Networks. WEB 2008. Lecture Notes in Business Information Processing, vol 22. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01256-3_14
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DOI: https://doi.org/10.1007/978-3-642-01256-3_14
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