Keyword Searching and Browsing in Databases using BANKS
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
A Unified Probabilistic Framework for Web Page Scoring Systems
IEEE Transactions on Knowledge and Data Engineering
Ontology summarization based on rdf sentence graph
Proceedings of the 16th international conference on World Wide Web
Automatic summarising: The state of the art
Information Processing and Management: an International Journal
Identifying Potentially Important Concepts and Relations in an Ontology
ISWC '08 Proceedings of the 7th International Conference on The Semantic Web
ASWC '08 Proceedings of the 3rd Asian Semantic Web Conference on The Semantic Web
Snippet Generation for Semantic Web Search Engines
ASWC '08 Proceedings of the 3rd Asian Semantic Web Conference on The Semantic Web
LexRank: graph-based lexical centrality as salience in text summarization
Journal of Artificial Intelligence Research
Using Naming Authority to Rank Data and Ontologies for Web Search
ISWC '09 Proceedings of the 8th International Semantic Web Conference
RDFSync: efficient remote synchronization of RDF models
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Evaluations of user-driven ontology summarization
EKAW'10 Proceedings of the 17th international conference on Knowledge engineering and management by the masses
Generating summaries for ontology search
Proceedings of the 20th international conference companion on World wide web
Finding and ranking knowledge on the semantic web
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
Finding important vocabulary within ontology
ASWC'06 Proceedings of the First Asian conference on The Semantic Web
Combining query translation with query answering for efficient keyword search
ESWC'10 Proceedings of the 7th international conference on The Semantic Web: research and Applications - Volume Part II
Hi-index | 0.00 |
When searching for RDF vocabularies, users often feel hindered by the lengthy description of a retrieved vocabulary from judging its relevance. A natural strategy for dealing with this issue is to generate a summary of the vocabulary description that compactly carries its main theme and reveals its relevance to the user's information need. In this paper, we present a new solution to this problem of vocabulary summarization, which has been defined as ranking and selecting RDF sentences in our previous work. Firstly, we propose a novel bipartite graph representation of vocabulary description, on which we carry out a stochastic analysis of a random surfer's behavior, from which we derive a new centrality measure for RDF sentences called BipRank. Further, we improve it by investigating the patterns of RDF sentences and employing their statistical features. Then, we combine BipRank with query relevance and cohesion metrics into an aggregate objective function to be optimized for the selection of RDF sentences. Our experiments on real-world vocabularies demonstrate the superiority of our approach to the baseline, and also validate its scalability in practice.