Semantic Web-Based Knowledge Acquisition Using Key Events from News

Frederik Hogenboom, Flavius Frasincar, U Kaymak

Research output: Contribution to conferenceAbstractAcademic

Abstract

Due to the ever increasing need for information, it is vital to stay up-to-date with emerging events. Common sources of information are news messages, which contain events that could be of importance for people. Hermes is an ontology-based framework for building news personalization services, which focuses on news classification and knowledge base updating. Furthermore, the framework allows for news querying and result presentation. In this paper, we focus on the techniques involved in keeping Hermes' internal knowledge base up-to-date. Essentially, our semi-automatic approach to knowledge acquisition from news is based on ontologies and lexico-semantic patterns. Experiments with an implementation of the framework, the Hermes News Portal (HNP), show for news classification a precision and recall of 86% and 81%, respectively. Usability tests demonstrate that user interaction with the system, needed for knowledge base updating, is positively assessed by the users.
Original languageEnglish
Pages261-262
Number of pages2
Publication statusPublished - 25 Oct 2010
EventTwenty-Second Benelux Conference on Artificial Intelligence (BNAIC 2010) - Luxembourg, Luxembourg
Duration: 25 Oct 201026 Oct 2010

Conference

ConferenceTwenty-Second Benelux Conference on Artificial Intelligence (BNAIC 2010)
CityLuxembourg, Luxembourg
Period25/10/1026/10/10

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