Inference networks for document retrieval
SIGIR '90 Proceedings of the 13th annual international ACM SIGIR conference on Research and development in information retrieval
Evaluation of an inference network-based retrieval model
ACM Transactions on Information Systems (TOIS) - Special issue on research and development in information retrieval
Relevance feedback and inference networks
SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Document filtering with inference networks
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Inductive learning algorithms and representations for text categorization
Proceedings of the seventh international conference on Information and knowledge management
A flexible model for retrieval of SGML documents
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Link-based and content-based evidential information in a belief network model
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Modern Information Retrieval
Searching web databases by structuring keyword-based queries
Proceedings of the eleventh international conference on Information and knowledge management
Combining link-based and content-based methods for web document classification
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
The effectiveness of automatically structured queries in digital libraries
Proceedings of the 4th ACM/IEEE-CS joint conference on Digital libraries
Explorer's Guide to the Semantic Web
Explorer's Guide to the Semantic Web
Query expansion in information retrieval systems using a Bayesian network-based thesaurus
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Ontology-Based Natural Query Retrieval Using Conceptual Graphs
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Expanded information retrieval using full-text searching
Journal of Information Science
Quantifying the impact of concept recognition on biomedical information retrieval
Information Processing and Management: an International Journal
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Information retrieval (IR) with metadata tends to have high precision as long as the user expresses the information need accurately but may suffer from low recall because queries are too exact with the specification of the metadata fields. On the other hand, full-text retrieval tends to suffer more from low precision especially when queries are simple and the number of documents is large. While structured queries targeted at metadata can be quite precise and the retrieval results can be accurate, it is not easy to construct an effective structured query without understanding the characteristics of the metadata. Casual users, however, are usually interested in spending time to understand the meaning of various metadata. In this paper, we propose a hybrid IR model that searches both metadata and text fields of documents. User queries are analyzed and converted into a hybrid query automatically. Experiments show that the hybrid approach outperforms either of the cases, i.e. searching text only or metadata only.