Fast and effective query refinement
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
Hierarchical faceted metadata in site search interfaces
CHI '02 Extended Abstracts on Human Factors in Computing Systems
Faceted metadata for image search and browsing
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
An Approach to Integrating Query Refinement in SQL
EDBT '02 Proceedings of the 8th International Conference on Extending Database Technology: Advances in Database Technology
Automatic categorization of query results
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Clustering versus faceted categories for information exploration
Communications of the ACM - Supporting exploratory search
Probabilistic information retrieval approach for ranking of database query results
ACM Transactions on Database Systems (TODS)
Towards keyword-driven analytical processing
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
BANKS: browsing and keyword searching in relational databases
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Efficient IR-style keyword search over relational databases
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Authority-based keyword search in databases
ACM Transactions on Database Systems (TODS)
Minimum-effort driven dynamic faceted search in structured databases
Proceedings of the 17th ACM conference on Information and knowledge management
BioNav: Effective Navigation on Query Results of Biomedical Databases
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Measure-driven keyword-query expansion
Proceedings of the VLDB Endowment
The semantic GrowBag algorithm: automatically deriving categorization systems
ECDL'07 Proceedings of the 11th European conference on Research and Advanced Technology for Digital Libraries
Query expansion based on clustered results
Proceedings of the VLDB Endowment
Facet discovery for structured web search: a query-log mining approach
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
The economics in interactive information retrieval
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Exploiting available memory and disk for scalable instant overview search
WISE'11 Proceedings of the 12th international conference on Web information system engineering
ReDRIVE: result-driven database exploration through recommendations
Proceedings of the 20th ACM international conference on Information and knowledge management
TEXplorer: keyword-based object search and exploration in multidimensional text databases
Proceedings of the 20th ACM international conference on Information and knowledge management
Differentiating search results on structured data
ACM Transactions on Database Systems (TODS)
Multi-select faceted navigation based on minimum description length principle
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
Comprehension-based result snippets
Proceedings of the 21st ACM international conference on Information and knowledge management
Semantic Query Expansion using Cluster Based Domain Ontologies
International Journal of Information Retrieval Research
YmalDB: a result-driven recommendation system for databases
Proceedings of the 16th International Conference on Extending Database Technology
Journal of Web Engineering
Automated faceted reporting for web analytics
Proceedings of the 4th international workshop on Web-scale knowledge representation retrieval and reasoning
A probabilistic optimization framework for the empty-answer problem
Proceedings of the VLDB Endowment
YmalDB: exploring relational databases via result-driven recommendations
The VLDB Journal — The International Journal on Very Large Data Bases
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Faceted navigation is being increasingly employed as an effective technique for exploring large query results on structured databases. This technique of mitigating information-overload leverages metadata of the query results to provide users with facet conditions that can be used to progressively refine the user's query and filter the query results. However, the number of facet conditions can be quite large, thereby increasing the burden on the user. We present the FACeTOR system that proposes a cost-based approach to faceted navigation. At each step of the navigation, the user is presented with a subset of all possible facet conditions that are selected such that the overall expected navigation cost is minimized and every result is guaranteed to be reachable by a facet condition. We prove that the problem of selecting the optimal facet conditions at each navigation step is NP-Hard, and subsequently present two intuitive heuristics employed by FACeTOR. Our user study at Amazon Mechanical Turk shows that FACeTOR reduces the user navigation time compared to the cutting edge commercial and academic faceted search algorithms. The user study also confirms the validity of our cost model. We also present the results of an extensive experimental evaluation on the performance of the proposed approach using two real datasets. FACeTOR is available at http://db.cse.buffalo.edu/facetor/.