2008 | OriginalPaper | Buchkapitel
Q2Semantic: A Lightweight Keyword Interface to Semantic Search
verfasst von : Haofen Wang, Kang Zhang, Qiaoling Liu, Thanh Tran, Yong Yu
Erschienen in: The Semantic Web: Research and Applications
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
The increasing amount of data on the Semantic Web offers opportunities for semantic search. However, formal query hinders the casual users in expressing their information need as they might be not familiar with the query’s syntax or the underlying ontology. Because keyword interfaces are easier to handle for casual users, many approaches aim to translate keywords to formal queries. However, these approaches yet feature only very basic query ranking and do not scale to large repositories. We tackle the scalability problem by proposing a novel clustered-graph structure that corresponds to only a summary of the original ontology. The so reduced data space is then used in the exploration for the computation of top-
k
queries. Additionally, we adopt several mechanisms for query ranking, which can consider many factors such as the query length, the relevance of ontology elements w.r.t. the query and the importance of ontology elements. The experimental results performed against our implemented system Q2Semantic show that we achieve good performance on many datasets of different sizes.