Public procurement is the purchase of goods and services by a public authority. Open tendering opens up sufficient and fair competition between suppliers and ensures that public contracts are awarded fairly, transparently and without discrimination. A public e-procurement platform allows to reach these objectives through a public tendering e-marketplace. Tender notices can be used to search for business opportunities. Tendering websites provide keyword-based search and category-based notifications to the subscribers. The idea is that notification systems deliver tender opportunities to the suppliers and thus reduce the amount of time spent looking for these tenders. But according to potential wide range of products in a business sector, a supplier may receive an extensive list of notifications which makes it difficult to find the best matched opportunities with the supplier’s product portfolio. Semantic-based technologies can be used to improve the search performance. In a previous work, a matching mechanism was developed to measure the similarity ratio of providers’ product e-catalogues with a buyer’s request. The matching mechanism uses domain ontologies to discover the semantic relationships among product data. In this paper, this product search approach is applied to a public tendering website, called Tenders Electronic Daily, in order to improve opportunity search service. The results show that the matching mechanism improves precision and recall measures.