Published: 2013 Dezember
Institution: Institut AIFB, KIT
Erscheinungsort / Ort: Karlsruhe
To allow search on the Web of data, systems have to combine data from multiple sources. However, to effectively fulfill user information needs, systems must be able to “look beyond” exactly matching data sources and offer information from additional/contextual sources (data source contextualization). For this, users should be involved in the source selection process – choosing which sources contribute to their search results. Previous work, however, solely aims at source contextualization for “Web tables”, while relying on schema information and simple relational entities. Addressing these shortcomings, we exploit work from the field of data mining and show how to enable Web data source contextualization. Based on a real-world use case, we built a prototype contextualization engine, which we integrated in a system for searching the Web of data. We empirically validated the effectiveness of our approach – achieving performance gains of up to 29% over the state-of-the-art.