In this paper, we develop a decision-theoretic framework for ordering candidate matches for user confirmation using the concept of the value of perfect information (VPI). At the core of this concept is a utility function that quantifies the desirability of a given state; thus, we devise a utility function for dataspaces based on query result quality. We show in practice how to efficiently apply VPI in concert with this utility function to order user confirmations. A detailed experimental evaluation on both real and synthetic datasets shows that the ordering of user feedback produced by this VPI-based approach yields a dataspace with a significantly higher utility than a wide range of other ordering strategies. Finally, we outline the design of Roomba, a system that utilizes this decision-theoretic framework to guide a dataspace in soliciting user feedback in a pay-as-you-go manner.}, acmid = {1376701}, address = {New York, NY, USA}, author = {Jeffery, Shawn R. and Franklin, Michael J. and Halevy, Alon Y.}, booktitle = {Proceedings of the 2008 ACM SIGMOD international conference on Management of data}, doi = {10.1145/1376616.1376701}, interhash = {3ceaf563712b776c1ed97a8cb061f63b}, intrahash = {3bff24fb9eb1e39fa97a524aabb8dee9}, isbn = {978-1-60558-102-6}, location = {Vancouver, Canada}, numpages = {14}, pages = {847--860}, publisher = {ACM}, title = {Pay-as-you-go user feedback for dataspace systems}, url = {http://doi.acm.org/10.1145/1376616.1376701}, year = 2008 } @article{doan2011crowdsourcing, abstract = {The practice of crowdsourcing is transforming the Web and giving rise to a new field.}, acmid = {1924442}, address = {New York, NY, USA}, author = {Doan, Anhai and Ramakrishnan, Raghu and Halevy, Alon Y.}, doi = {10.1145/1924421.1924442}, interhash = {6dbf364159ce568b92727145a3fca85e}, intrahash = {84f738a6efae5eb6612ea75e8616fecf}, issn = {0001-0782}, issue_date = {April 2011}, journal = {Communications of the ACM}, month = apr, number = 4, numpages = {11}, pages = {86--96}, publisher = {ACM}, title = {Crowdsourcing systems on the World-Wide Web}, url = {http://doi.acm.org/10.1145/1924421.1924442}, volume = 54, year = 2011 } @article{375731, abstract = {A data-integration system provides access to a multitude of data sources through a single mediated schema. A key bottleneck in building such systems has been the laborious manual construction of semantic mappings between the source schemas and the mediated schema. We describe LSD, a system that employs and extends current machine-learning techniques to semi-automatically find such mappings. LSD first asks the user to provide the semantic mappings for a small set of data sources, then uses these mappings together with the sources to train a set of learners. Each learner exploits a different type of information either in the source schemas or in their data. Once the learners have been trained, LSD finds semantic mappings for a new data source by applying the learners, then combining their predictions using a meta-learner. To further improve matching accuracy, we extend machine learning techniques so that LSD can incorporate domain constraints as an additional source of knowledge, and develop a novel learner that utilizes the structural information in XML documents. Our approach thus is distinguished in that it incorporates multiple types of knowledge. Importantly, its architecture is extensible to additional learners that may exploit new kinds of information. We describe a set of experiments on several real-world domains, and show that LSD proposes semantic mappings with a high degree of accuracy.}, address = {New York, NY, USA}, author = {Doan, AnHai and Domingos, Pedro and Halevy, Alon Y.}, doi = {http://doi.acm.org/10.1145/376284.375731}, interhash = {1550f1948858bf8b315ea2fc6ed789cd}, intrahash = {29e7660361ca79b97b00e5db51fb66ee}, issn = {0163-5808}, journal = {SIGMOD Rec.}, number = 2, pages = {509--520}, publisher = {ACM}, title = {Reconciling schemas of disparate data sources: a machine-learning approach}, url = {http://portal.acm.org/citation.cfm?id=375731&dl=GUIDE&coll=GUIDE&CFID=75153142&CFTOKEN=89522229}, volume = 30, year = 2001 } @inproceedings{conf/sigmod/LeeDDHD04, author = {Dhamankar, Robin and Lee, Yoonkyong and Doan, AnHai and Halevy, Alon Y. and Domingos, Pedro}, booktitle = {SIGMOD Conference}, crossref = {conf/sigmod/2004}, date = {2005-02-21}, editor = {Weikum, Gerhard and König, Arnd Christian and Deßloch, Stefan}, ee = {http://doi.acm.org/10.1145/1007568.1007612}, interhash = {ec92ce1b40894b75fb11d45037a54a7c}, intrahash = {fa94bc508e9954107e8603527b66dcb7}, isbn = {1-58113-859-8}, pages = {383-394}, publisher = {ACM}, title = {iMAP: Discovering Complex Mappings between Database Schemas.}, url = {http://www.cs.washington.edu/homes/pedrod/papers/sigmod04.pdf}, year = 2004 } @inproceedings{doan02learning, address = {Honolulu, Hawaii, USA}, author = {Doan, AnHai and Madhavan, Jayant and Domingos, Pedro and Halevy, Alon}, booktitle = {Proceedings to the Eleventh International World Wide}, interhash = {7e4b3e995ef04182c07c14b5988777dc}, intrahash = {b7a6ffa062893317d477dc8edcc17115}, month = May, title = {Learning to Map between Ontologies on the Semantic Web}, url = {http://www.cs.washington.edu/homes/alon/site/files/glue.pdf}, year = 2002 } @inproceedings{halevymadhavan2003, author = {Halevy, Alon Y. and Madhavan, Jayant}, bibsource = {DBLP, http://dblp.uni-trier.de}, booktitle = {IJCAI-03, Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, Acapulco, Mexico, August 9-15, 2003}, editor = {Gottlob, Georg and Walsh, Toby}, interhash = {296e995087df1b2d67f0ceb22510aa58}, intrahash = {75d3c0fdd9fdbbfebd93cfda1ee42d28}, pages = {1567-1572}, publisher = {Morgan Kaufmann}, title = {Corpus-Based Knowledge Representation}, year = 2003 }