Electronic commerce: a manager's guide
Electronic commerce: a manager's guide
Automated ontology construction for unstructured text documents
Data & Knowledge Engineering
A Virtual Catalog Generated from Web Pages of Vendors for Comparative Shopping
ITNG '07 Proceedings of the International Conference on Information Technology
Ontology-based information content computation
Knowledge-Based Systems
GMQL: A graphical multimedia query language
Knowledge-Based Systems
A high-performance FAQ retrieval method using minimal differentiator expressions
Knowledge-Based Systems
A New Model to Compute the Information Content of Concepts from Taxonomic Knowledge
International Journal on Semantic Web & Information Systems
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The evolution of Business-to-Consumer (B2C) eCommerce has been formed through various generations. Last models of B2C eCommerce are comparative shopping systems that connect to multiple vendors' databases and collect the information requested by the user. The comparative result obtained is then displayed in a tabular format in the user's browser. Although this scenario is much better than the multiple manual site comparisons, user still needs to face inconsistent user interfaces when he is linked from the comparison site to the actual purchasing site for shopping. Therefore, user has to learn logics of each site's user interface. In this paper, we propose a question answering system based on natural language processing techniques for retail (B2C) in eCommerce. This system gets a question in natural language formats, decomposes it to keywords, and extracts constraints automatically. Corresponding answers are then retrieved from the vendors' Web sites by exploiting the question constraints.