Learning Information Extraction Rules for Semi-Structured and Free Text
Machine Learning - Special issue on natural language learning
Intelligent crawling on the World Wide Web with arbitrary predicates
Proceedings of the 10th international conference on World Wide Web
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We propose a tool for the discovery of business opportunities on the Web, more specifically to help a user find relevant call for tenders (CFT), i.e. invitations to contractors to submit a tender for their products/services. Simple keyword-based Information Retrieval do not capture the relationships in the data, which are needed to answer the complex needs of the users. We therefore augment keywords with information extracted through natural language processing and business intelligence tools. As opposed to most systems, this information is used at all stages in the back-end and interface. The benefits are twofold: first we obtain higher precision of search and classification, and second the user gains access to a deeper level of information.