Discussions on Subgraph Ranking for Keyworded Search
Justin Song, Inkyo Kang, Wookey Lee, Jinho Kim, Jooyeon Lee · 2018
Recently many graph information can be available in numerous application domains, including relational database s, Web, Bioinformatics, Chemistry reaction information, Ontology, XML, Social Networks, Patent Information, Paper citation, and RDF graphs, etc. Graphs also have structure to be found to express complicate data relationships like Web, Database, XML Document and Semantic Web. Traditionally, user had to learn difficult query languages like SQL to do information search over graph structures. There are needs to find out a simple and effective keyword search method for non-technical users so as to use a keyword search method on the ever-increasing graph data. The purpose of this research is to develop a method for ranking over the graph structures. We propose the relevance score for each node and link by using each query keyword.