Paper Info
Title
A linear and monotonic strategy to keyword search over RDF data
Abstract
Keyword-based search over (semi)structured data is today considered an essential feature of modern information management systems and has become an hot topic in database research and development. Most of the recent approaches to this problem refer to a general scenario where: (i) the data source is represented as a graph, (ii) answers to queries are sub-graphs of the source containing keywords from queries, and (iii) solutions are ranked according to a relevance criteria. In this paper, we illustrate a novel approach to keyword search over semantic data that combines a solution building algorithm and a ranking technique to generate the best results in the first answers generated. We show that our approach is monotonic and has a linear computational complexity, greatly reducing the complexity of the overall process. Finally, experiments demonstrate that our approach exhibits very good efficiency and effectiveness, especially with respect to competing approaches.
Year
DOI
Venue
2013
10.1007/978-3-642-39200-9_28
ICWE
Keywords
Field
DocType
novel approach,rdf data,recent approach,best result,semantic data,database research,structured data,keyword-based search,essential feature,monotonic strategy,linear computational complexity,data source
Monotonic function,Data mining,Management information systems,World Wide Web,Information retrieval,Ranking,Computer science,Keyword search,Data model,RDF,Computational complexity theory,Semantic data model
Conference
Citations 
PageRank 
References 
6
0.51
15
Authors
3
Name
Order
Citations
PageRank
Roberto De Virgilio120227.46
Antonio Maccioni28011.59
Paolo Cappellari317512.52