Using RDF Summary Graph For Keyword-based Semantic Searches

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.

[1]  Haofen Wang,et al.  Top-k Exploration of Query Candidates for Efficient Keyword Search on Graph-Shaped (RDF) Data , 2009, 2009 IEEE 25th International Conference on Data Engineering.

[2]  Hans Peter Luhn,et al.  A Statistical Approach to Mechanized Encoding and Searching of Literary Information , 1957, IBM J. Res. Dev..

[3]  Pierre Zweigenbaum,et al.  Medical question answering: translating medical questions into sparql queries , 2012, IHI '12.

[4]  Kalina Bontcheva,et al.  A Natural Language Query Interface to Structured Information , 2008, ESWC.

[5]  Austin Melton,et al.  Automatic Weight Generation and Class Predicate Stability in RDF Summary Graphs , 2015, IESD@ISWC.

[6]  Sebastian Hellmann,et al.  Keyword-Driven SPARQL Query Generation Leveraging Background Knowledge , 2011, 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology.

[7]  Jens Lehmann,et al.  DBpedia: A Nucleus for a Web of Open Data , 2007, ISWC/ASWC.

[8]  Ruoming Jin,et al.  Axiomatic ranking of network role similarity , 2011, KDD.

[9]  Frank van Harmelen,et al.  Sesame: A Generic Architecture for Storing and Querying RDF and RDF Schema , 2002, SEMWEB.

[10]  Praveen Paritosh,et al.  Freebase: a collaboratively created graph database for structuring human knowledge , 2008, SIGMOD Conference.

[11]  Tim Berners-Lee,et al.  Linked Data - The Story So Far , 2009, Int. J. Semantic Web Inf. Syst..

[12]  Ollivier Haemmerlé,et al.  A Semantic Web Interface Using Patterns: The SWIP System , 2011, GKR.

[13]  Jens Lehmann,et al.  AutoSPARQL: Let Users Query Your Knowledge Base , 2011, ESWC.

[14]  Austin Melton,et al.  Building Summary Graphs of RDF Data in Semantic Web , 2015, 2015 IEEE 39th Annual Computer Software and Applications Conference.

[15]  Kemafor Anyanwu,et al.  Effectively Interpreting Keyword Queries on RDF Databases with a Rear View , 2011, International Semantic Web Conference.

[16]  Karen Spärck Jones.  A statistical interpretation of term specificity and its application in retrieval , 2021, J. Documentation.

[17]  Enrico Motta,et al.  SemSearch: A Search Engine for the Semantic Web , 2006, EKAW.

[18]  Fleur Mougin,et al.  Natural Language Question Analysis for Querying Biomedical Linked Data , 2014 .

[19]  Tom Fawcett,et al.  An introduction to ROC analysis , 2006, Pattern Recognit. Lett..

[20]  Jens Lehmann,et al.  Template-based question answering over RDF data , 2012, WWW.

[21]  Peter Mika,et al.  Ad-hoc object retrieval in the web of data , 2010, WWW '10.

[22]  Deborah L. McGuinness,et al.  OWL Web ontology language overview , 2004 .