Effective retrieval with distributed collections
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
GlOSS: text-source discovery over the Internet
ACM Transactions on Database Systems (TODS)
Query-based sampling of text databases
ACM Transactions on Information Systems (TOIS)
Approaches to collection selection and results merging for distributed information retrieval
Proceedings of the tenth international conference on Information and knowledge management
Evolution strategies –A comprehensive introduction
Natural Computing: an international journal
Ontology Learning for the Semantic Web
IEEE Intelligent Systems
PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
When one sample is not enough: improving text database selection using shrinkage
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Ontology Evolution: Not the Same as Schema Evolution
Knowledge and Information Systems
Information source selection for resource constrained environments
ACM SIGMOD Record
Adaptive query-based sampling for distributed IR
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Consensus-based evaluation framework for distributed information retrieval systems
Knowledge and Information Systems
Learning and inferencing in user ontology for personalized Semantic Web search
Information Sciences: an International Journal
Reusing ontology mappings for query routing in semantic peer-to-peer environment
Information Sciences: an International Journal
A framework for ontology evolution in collaborative environments
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
Consistent evolution of OWL ontologies
ESWC'05 Proceedings of the Second European conference on The Semantic Web: research and Applications
A survey of schema-based matching approaches
Journal on Data Semantics IV
Semantic overlay networks for p2p systems
AP2PC'04 Proceedings of the Third international conference on Agents and Peer-to-Peer Computing
Ontology-based concept similarity in Formal Concept Analysis
Information Sciences: an International Journal
Collaborative browsing system based on semantic mashup with open APIs
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Cross-lingual query expansion in multilingual folksonomies: A case study on Flickr
Knowledge-Based Systems
Semantics enhanced engineering and model reasoning for control application development
Multimedia Tools and Applications
Relational large scale multi-label classification method for video categorization
Multimedia Tools and Applications
Multimedia Tools and Applications
Tuning user profiles based on analyzing dynamic preference in document retrieval systems
Multimedia Tools and Applications
Preference-based user rating correction process for interactive recommendation systems
Multimedia Tools and Applications
Ontology-based access control model for security policy reasoning in cloud computing
The Journal of Supercomputing
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Metadata about information sources (e.g., databases and repositories) can be collected by Query Sampling (QS). Such metadata can include topics and statistics (e.g., term frequencies) about the information sources. This provides important evidence for determining which sources in the distributed information space should be selected for a given user query. The aim of this paper is to find out the semantic relationships between the information sources in order to distribute user queries to a large number of sources. Thereby, we propose an evolutionary approach for automatically conducting QS using multiple crawlers and obtaining the optimized semantic network from the sources. The aim of combining QS and evolutionary methods is to collaboratively extract metadata about target sources and optimally integrate the metadata, respectively. For evaluating the performance of contextualized QS on 122 information sources, we have compared the ranking lists recommended by the proposed method with user feedback (i.e., ideal ranks), and also computed the precision of the discovered subsumptions in terms of the semantic relationships between the target sources.