2017/07/12 by Serkan Ayvaz, Ayvaz, Serkan, Mehmet Aydar +1
Computer Science · #Advanced Text Analysis Techniques #Artificial Intelligence (cs.AI) #Databases (cs.DB) #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Semantic Web and Ontologies #Web Data Mining and Analysis #cs.AI #cs.DB #cs.IR
paper · pdf · doi:10.48550/arxiv.1707.03602
5th International Conference on Advanced Technology & Sciences (ICAT'17). Istanbul, 2017
arxiv created 2017/07/12 · openalex publication_date 2017/07/12 · arxiv updated 2017/07/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The Semantic Web began to emerge as its standards and technologies developed rapidly in the recent years. The continuing development of Semantic Web technologies has facilitated publishing explicit semantics with data on the Web in RDF data model. This study proposes a semantic search framework to support efficient keyword-based semantic search on RDF data utilizing near neighbor explorations. The framework augments the search results with the resources in close proximity by utilizing the entity type semantics. Along with the search results, the system generates a relevance confidence score measuring the inferred semantic relatedness of returned entities based on the degree of similarity. Furthermore, the evaluations assessing the effectiveness of the framework and the accuracy of the results are presented.