A semantic web-based approach for personalizing news

Hermes is an ontology-based framework for building news personalization services. This framework consists of a news classification phase, which classifies the news, a knowledge base updating phase, which keeps the knowledge base up-to-date, a news querying phase, allowing the user to search the news for concepts of interest, and a results presentation phase, showing the returned news items. The focus of this paper is on how to keep the knowledge base up-to-date. For this purpose, we elaborate on the updating phase that searches for key events in the news. Using rules based on patterns and actions, these events can be extracted and the knowledge base is updated. This is a semi-automatic process since user validation is required before updating the knowledge base.

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