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Query Rewriting for Extracting Data Behind HTML Forms

This study explores query rewriting to extract data from HTML forms. A system is developed to create forms based on application-specific ontology analysis for efficient data retrieval and processing.

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Query Rewriting for Extracting Data Behind HTML Forms

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  1. Query Rewriting for Extracting Data Behind HTML Forms Xueqi Chen Department of Computer Science Brigham Young University March, 2003 Funded by National Science Foundation

  2. Motivation • Web information is stored in databases • Databases are accessed through forms • Automated agents are of great value • Process is difficult because of nature of forms

  3. Input Analyzer Extracted Information Application Ontology Site Form User Query Retrieved Page(s) Output Analyzer System Flowchart

  4. User Query Acquisition • Our system provides a form created based on application-specific ontology

  5. Site Form Analysis • Understand type, name, and/or values for each field

  6. Form Filling • Name matching • Regular Expressions – for fields with values provided • Stemming • Levenshtein Edit Distance • Longest Common Subsequences • Soundex • Wordnet • Value matching

  7. Value Matching: Case 1

  8. ? ? Value Matching: Case 2

  9. ? ? Value Matching: Case 3 Color?

  10. Value Matching: Case 4

  11. Value Matching: Case 5 ?

  12. Value Matching: Case 6

  13. Value Matching: Case 7

  14. Measurements • Matching Efficiency • Submission Efficiency • Post-processing Efficiency

  15. Measurements (cont’) • Matching Efficiency

  16. Measurements (cont’) • Matching Efficiency • Submission Efficiency

  17. Measurements (cont’) • Matching Efficiency • Submission Efficiency • Post-processing Efficiency

  18. Contributions • It enhances the effectiveness of the data-extraction process • It presents another technique, in addition to [RGa01], to access data behind HTML forms.

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