A query language and ranking algorithm for news items in the Hermes news processing framework

Hermes is a Web-based framework that makes use of many Semantic Web technologies for building personalized news services. Ontologies are employed for knowledge representation, natural language processing techniques are used for semantic text analysis, and semantic query languages enable the specification of the desired information. To accommodate for the need for an intuitive way to create complex queries for news information, we present the Hermes Graphical Query Language (HGQL). The language enables users to create structured queries that use disjunctive, conjunctive, negation, and pattern operators. In addition, this paper presents a ranking algorithm based on the queries made using our graphical query language. Results show that our proposed ranking algorithm significantly outperforms three state-of-the-art ranking algorithms and that users prefer our graphical query language over a text-based alternative.

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