1 Semi-Automatic Semantic Annotation for Hidden-Web Tables Cui Tao & David W. Embley Data Extraction Research Group Department of Computer Science Brigham Young University Supported by NSF

2 Semantic Annotation  The Hidden Web:  Hidden behind forms  Hard to query “cdk-4"

3 Semantic Annotation  The Hidden Web:  Hidden behind forms  Hard to query to find the protein and the animo-acids information for gene “cdk-4"

4 Semantic Annotation  The Hidden Web:  Hidden behind forms  Hard to query  Semantic annotation  Machine-”understandable”  Publicly accessible

5 System Overview  Initial semantic annotation  Manually annotate a sample page  With respect to a selected ontology  Table interpretation  Automatic  Tables from hidden web pages  Final semantic annotation  Automatic  Annotate interpreted tables

6 Initial Semantic Annotation  SMORE: Semantic Markup, Ontology and RDF Editor [Maryland information and network dynamics lab]

7

8 Table Interpretation  Table interpretation  Locate label and value  Pair label-value pairs  Remember path  TISP – Table Interpretation by Sibling Pages

9 TISP

10 Interpretation Technique: Sibling Page Comparison Same

11 Interpretation Technique: Sibling Page Comparison Almost Same

12 Interpretation Technique: Sibling Page Comparison Different Same

13 Interpretation Technique: Sibling Page Comparison Label Path = Identification.Gene model(s).Gene Model Xpath = html[1]/…/table[3]/tr[1]/td[2]/table[1]/tr[6]/td[2]/table[1]/tr[2]/td[1] Structure Pattern of a Table

14 Annotation Protein Name

15 Annotation – Split Nucleotide Size

16 Annotation – Merge Protein Information

17 Annotation—Union Name

18 Annotation—Selection Molecular Function

19 Generated RDF Annotation

20 Querying Annotated Data to find the protein and the animo-acids information for gene “cdk-4"

21 Summary  Semi-automatic semantic annotation for hidden web tables  Facilitate large-scale annotation to the web