Exploring Term Networks for Semantic Search over RDF Knowledge Graphs
Information retrieval approaches are considered as a key technology to empower lay users to access the Web of Data. A large number of related approaches such as Question Answering and Semantic Search have been developed to address this problem. While Question Answering promises more accurate results by returning a specific answer, Semantic Search engines are designed to retrieve the best top (K\ ranked resources. In this work, we propose *path, a Semantic Search approach that explores term networks for querying RDF knowledge graphs. The adequacy of the approach is evaluated employing benchmark datasets against state of the art Question Answering as well as Semantic Search systems. The results show that *path achieves better F\(_1\ score than the currently best performing Semantic Search system.
MTSR