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Understanding query interfaces by statistical parsing

Authors:

Frederick H. Lochovsky,

Tianqiang HuangAuthors Info & Claims

ACM Transactions on the Web (TWEB), Volume 7, Issue 2

Article No.: 8, Pages 1 - 22

https://doi.org/10.1145/2460383.2460387

Published: 29 May 2013 Publication History

Abstract

Users submit queries to an online database via its query interface. Query interface parsing, which is important for many applications, understands the query capabilities of a query interface. Since most query interfaces are organized hierarchically, we present a novel query interface parsing method, StatParser (Statistical Parser), to automatically extract the hierarchical query capabilities of query interfaces. StatParser automatically learns from a set of parsed query interfaces and parses new query interfaces. StatParser starts from a small grammar and enhances the grammar with a set of probabilities learned from parsed query interfaces under the maximum-entropy principle. Given a new query interface, the probability-enhanced grammar identifies the parse tree with the largest global probability to be the query capabilities of the query interface. Experimental results show that StatParser very accurately extracts the query capabilities and can effectively overcome the problems of existing query interface parsers.

References

[1]

Barbosa, L. and Freire, J. 2007a. An adaptive crawler for locating hidden-web entry points. In Proceedings of the 16^th International Conference on World Wide Web (WWW'07). ACM Press, New York, 441--450.

Digital Library

[2]

Barbosa, L. and Freire, J. 2007b. Combining classifiers to identify online databases. In Proceedings of the 16^th International Conference on World Wide Web (WWW'07). ACM Press, New York, 431--440.

Digital Library

[3]

Benslimane, S. M., Malki, M., Rahmouni, M. K., and Benslimane, D. 2007. Extracting personalized ontology from data-intensive web application: An html forms-based reverse engineering approach. Informatica 18, 4, 511--534.

Digital Library

[4]

Bergman, M. K. 2001. White paper: The deep web: Surfacing hidden value. J. Electron. Publish. 7, 1.

[5]

Borthwick, A. 1999. A maximum entropy approach to named entity recognition. Doctoral dissertation, New York University, New York.

Digital Library

[6]

Chang, K. C.-C., He, B., Li, C., Patel, M., and Zhang, Z. 2004. Structured databases on the Web: Observations and implications. ACM SIGMOD Rec. 33, 3, 61--70.

Digital Library

[7]

Charniak, E. 2000. A maximum-entropy-inspired parser. In Proceedings of the 1^st North American Chapter of the Association for Computational Linguistics Conference (NAACL'00). Association for Computational Linguistics, 132--139.

Digital Library

[8]

Dragut, E. C., Kabisch, T., Yu, C., and Leser, U. 2009. A hierarchical approach to model web query interfaces for web source integration. Proc. VLDB Endow. 2, 1, 325--336.

Digital Library

[9]

Dragut, E. C., Meng, W., and Yu, C. T. 2012. Deep Web Query Interface Understanding and Integration. Morgan and Claypool Publishers, San Francisco, CA.

Digital Library

[10]

Dragut, E., Wu, W., Sistla, P., Yu, C., and Meng, W. 2006. Merging source query interfaces on web databases. In Proceedings of the 22^nd International Conference on Data Engineering (ICDE'06). IEEE Computer Society, 679--690.

Digital Library

[11]

Feiner, A., Kraus, S., and Korf, R. E. 2003. KBFS: K-best-first search. Ann. Math. Artif. Intell. 39, 1--2, 19--39.

Digital Library

[12]

Furche, T., Gottlob, G., Grasso, G., Guo, X., Orsi, G., and Schallhart, C. 2011. Real understanding of real estate forms. In Proceedings of the International Conference on Web Intelligence, Mining and Semantics (WIMS'11). ACM Press, New York.

Digital Library

[13]

Furche, T., Gottlob, G., Grasso, G., Guo, X., Orsi, G., and Schallhart, C. 2012. OPAL: Automated form understanding for the deep web. In Proceedings of the 21^st International Conference on World Wide Web (WWW'12). ACM Press, New York, 829--838.

Digital Library

[14]

Guo, X., Kranzdorf, J., Furche, T., Grasso, G., Orsi, G., and Schallhart, C. 2012. OPAL: A passepartout for web forms. In Proceedings of the 21^st International Conference Companion on World Wide Web. ACM Press, New York, 353--356.

Digital Library

[15]

He, B., Zhang, Z., and Chang, K. C.-C. 2005a. MetaQuerier: Querying structured web sources on-the-fly. In Proceedings of ACM SIGMOD Conference (SIGMOD'05). ACM Press, New York, 927--929.

Digital Library

[16]

He, H., Meng, W., Lu, Y., Yu, C., and Wu, Z. 2007. Towards deeper understanding of the search interfaces of the deep web. World Wide Web 10, 2, 133--155.

Digital Library

[17]

He, H., Meng, W., Lu, Y., Yu, C., and Wu, Z. 2005b. Constructing interface schemas for search interfaces of web databases. In Proceedings of the 6^th International Conference on Web Information Systems Engineering (WISE'05). Springer, 29--42.

Digital Library

[18]

Kaljuvee, O., Buyukkokten, O., Garcia-Molina, H., and Paepcke, A. 2001. Efficient web form entry on PDAs. In Proceedings of the 10^th International Conference on World Wide Web (WWW'01). ACM Press, New York, 663--672.

Digital Library

[19]

Khare, R. and An, Y. 2009. An empirical study on using hidden markov model for search interface segmentation. In Proceedings of the 18^th ACM Conference on Information and Knowledge Management (CIKM'09). ACM Press, New York, 17--26.

Digital Library

[20]

Khare, R., An, Y., and Song, I.-Y. 2010. Understanding deep web search interfaces: A survey. ACM SIGMOD Rec. 39, 1, 33--40.

Digital Library

[21]

Madhavan, J., Cohen, S., Dong, X. L., Halevy, A. Y., Jeffery, S. R., Ko, D., and Yu, C. 2007. Web-scale data integration: You can afford to pay as you go. In Proceedings of the 3^rd Biennial Conference on Innovative Data Systems Research (CIDR'07). 342--350.

[22]

Minka, T. P. 2003. A comparison of numerical optimizers for logistic regression. Tech. rep., Department of Statistics, Carnegie Mellon University. October.

[23]

Nguyen, H., Nguyen, T., and Freire, J. 2008. Learning to extract form labels. Proc. VLDB Endow. 1, 1, 684--694.

Digital Library

[24]

Raghavan, S. and Garcia-Molina, H. 2001. Crawling the hidden web. In Proceedings of the 27^th International Conference on Very Large Data Bases (VLDB'01). Morgan Kaufmann Publishers, San Francisco, CA, 129--138.

Digital Library

[25]

Ratnaparkhi, A. 1996. A maximum entropy model for part-of-speech tagging. In Proceedings of the 1^st Empirical Methods in Natural Language Processing Conference. 133--142.

[26]

Sheng, C., Zhang, N., Tao, Y., and Jin, X. 2012. Optimal algorithms for crawling a hidden database in the web. Proc. VLDB Endow. 5, 11, 1112--1123.

Digital Library

[27]

Shestakov, D., Bhowmick, S. S., and Lim, E.-P. 2005. DEQUE: Querying the deep web. Data Knowl. Engin. 52, 3, 273--311.

Digital Library

[28]

Su, W., Wang, J., and Lochovsky, F. H. 2006a. Automatic hierarchical classification of structured deep web databases. In Proceedings of the 7^th International Conference on Web Information Systems Engineering (WISE'06). Springer, 210--221.

Digital Library

[29]

Su, W., Wang, J., and Lochovsky, F. H. 2006b. Holistic schema matching for web query interfaces. In Proceedings of the 10^th International Conference on Extending Database Technology (EDBT'06). Springer, 77--94.

Digital Library

[30]

Su, W., Wang, J., and Lochovsky, F. H. 2009. ODE: Ontology-assisted data extraction. ACM Trans. Datab. Syst. 34, 2.

Digital Library

[31]

Vieira, K., Barbosa, L., Freire, J., and Silva, A. 2008. Siphon++: A hidden-web crawler for keyword-based interfaces. In Proceedings of the 17^th ACM Conference on Information and Knowledge Management (CIKM'08). ACM Press, New York, 1361--1362.

Digital Library

[32]

Wu, P., Wen, J.-R., Liu, H., and Ma, W.-Y. 2006. Query selection techniques for efficient crawling of structured web sources. In Proceedings of the 22^nd International Conference on Data Engineering (ICDE'06). IEEE Computer Society, 47--58.

Digital Library

[33]

Wu, W., Doan, A., Yu, C., and Meng, W. 2009. Modeling and extracting deep-web query interfaces. In Advances in Information and Intelligent Systems, Springer, 65--90.

[34]

Wu, W., Yu, C., Doan, A., and Meng, W. 2004. An interactive clustering-based approach to integrating source query interfaces on the deep web. In Proceedings of the ACM SIGMOD Conference (SIGMOD'04). ACM Press, New York, 95--106.

Digital Library

[35]

Zhang, T. and Oles, F. J. 2001. Text categorization based on regularized linear classification methods. Inf. Retr. 4, 1, 5--31.

Digital Library

[36]

Zhang, Z., He, B., and Chang, K. C.-C. 2004. Understanding web query interfaces: Best-effort parsing with hidden syntax. In Proceedings of ACM SIGMOD Conference on Management of Data (SIGMOD'04). ACM Press, New York, 107--118.

Digital Library

Cited By

Zhang SLi YYan WGuo YChen X(2021)Dependency-aware Form Understanding2021 IEEE 32nd International Symposium on Software Reliability Engineering (ISSRE)10.1109/ISSRE52982.2021.00026(139-149)Online publication date: Oct-2021
https://doi.org/10.1109/ISSRE52982.2021.00026
Hernandez JMarin-Castro HMorales-Sandoval M(2021)WebQuIn-LD: A Method of Integrating Web Query Interfaces Based on Linked DataIEEE Access10.1109/ACCESS.2021.31045249(115664-115675)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3104524
Hernández IRivero CRuiz D(2019)Deep Web crawlingWorld Wide Web10.1007/s11280-018-0602-122:4(1577-1610)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1007/s11280-018-0602-1
Show More Cited By

Index Terms

Understanding query interfaces by statistical parsing
1. Human-centered computing
  1. Human computer interaction (HCI)
2. Information systems
  1. Information retrieval

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Published In

cover image ACM Transactions on the Web

ACM Transactions on the Web Volume 7, Issue 2

May 2013

244 pages

ISSN:1559-1131

EISSN:1559-114X

DOI:10.1145/2460383

Issue’s Table of Contents

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 29 May 2013

Accepted: 01 January 2013

Revised: 01 October 2012

Received: 01 March 2012

Published in TWEB Volume 7, Issue 2

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Cited By

Zhang SLi YYan WGuo YChen X(2021)Dependency-aware Form Understanding2021 IEEE 32nd International Symposium on Software Reliability Engineering (ISSRE)10.1109/ISSRE52982.2021.00026(139-149)Online publication date: Oct-2021
https://doi.org/10.1109/ISSRE52982.2021.00026
Hernandez JMarin-Castro HMorales-Sandoval M(2021)WebQuIn-LD: A Method of Integrating Web Query Interfaces Based on Linked DataIEEE Access10.1109/ACCESS.2021.31045249(115664-115675)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3104524
Hernández IRivero CRuiz D(2019)Deep Web crawlingWorld Wide Web10.1007/s11280-018-0602-122:4(1577-1610)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1007/s11280-018-0602-1
Jou C(2019)Schema Extraction for Deep Web Query Interfaces Using Heuristics RulesInformation Systems Frontiers10.1007/s10796-018-9863-621:1(163-174)Online publication date: 1-Feb-2019
https://dl.acm.org/doi/10.1007/s10796-018-9863-6
Chahal PSingh MKumar S(2017)Semantic Analysis Based Approach for Relevant Text Extraction Using OntologyInternational Journal of Information Retrieval Research10.4018/IJIRR.20171001027:4(19-36)Online publication date: 1-Oct-2017
https://dl.acm.org/doi/10.4018/IJIRR.2017100102
Jou CCheng Y(2017)Heuristics-Based Schema Extraction for Deep Web Query Interfaces2017 IEEE International Conference on Information Reuse and Integration (IRI)10.1109/IRI.2017.80(389-396)Online publication date: Aug-2017
https://doi.org/10.1109/IRI.2017.80
Jou CDesai BToyoma M(2015)Semantics-Assisted Deep Web Query Interface ClassificationProceedings of the Eighth International C* Conference on Computer Science & Software Engineering10.1145/2790798.2790810(70-78)Online publication date: 13-Jul-2015
https://dl.acm.org/doi/10.1145/2790798.2790810
Furche TGottlob GGrasso GGuo XOrsi GSchallhart CWang C(2014)DIADEMProceedings of the VLDB Endowment10.14778/2733085.27330917:14(1845-1856)Online publication date: 1-Oct-2014
https://dl.acm.org/doi/10.14778/2733085.2733091
Su WLi YLochovsky FChung CBroder AShim KSuel T(2014)Query interfaces understanding by statistical parsingProceedings of the 23rd International Conference on World Wide Web10.1145/2567948.2579702(1291-1294)Online publication date: 7-Apr-2014
https://dl.acm.org/doi/10.1145/2567948.2579702
Furche TGottlob GGrasso GGuo XOrsi GSchallhart C(2013)The ontological keyThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-013-0323-022:5(615-640)Online publication date: 1-Oct-2013
https://dl.acm.org/doi/10.1007/s00778-013-0323-0

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