Name
Abstract | ||
|---|---|---|
Recently many graph information can be available in numerous application domains, including relational database s, Web, Bioinformatics, Chemistry reaction information, Ontol ogy, XML, Social Networks, Patent Information, Paper citatio n, and RDF graphs, etc. Graphs also have structure to be foun d 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 sear ch 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 gra ph data. The purpose of this research is to develop a method fo r ranking over the graph structures. We propose the relevance score for each node and link by using each query keyword. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/Cybermatics_2018.2018.00179 | 2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) |
Keywords | Field | DocType |
XML,Keyword search,Web pages,Databases,Search engines,Search problems | SQL,Query language,Search engine,XML,Web page,Information retrieval,Ranking,Relational database,Computer science,Semantic Web | Conference |
ISBN | Citations | PageRank |
978-1-5386-7975-3 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Justin J. Song | 1 | 0 | 0.34 |
| Inkyo Kang | 2 | 0 | 0.34 |
| Wookey Lee | 3 | 196 | 29.22 |
| Jinho Kim | 4 | 0 | 2.37 |
| Joo-Yeon Lee | 5 | 0 | 0.34 |