ODE: Ontology-Assisted Data Extraction Weifeng Su, Jiying Wang, Frederick H. Lochovsky Summarized by Joseph Park

Overview “Web databases…compose what is referred to as the deep Web” The goal of data extraction: – (1) Query result section identification - decides what section in a dynamically generated query result page contains the data that need to be extracted. – (2) Record segmentation - segments the query result section into records and extracts them. – (3) Data value alignment - aligns the data values from multiple records that belong to the same attribute so that they can be arranged into a table. – (4) Label assignment - assigns a suitable, meaningful label (i.e., an attribute name) to each column in an aligned table.

Problems Automatically extract data from query results Limitations of other systems: – Incapable of processing either zero or few query results. – Vulnerable to optional and disjunctive attributes. – Incapable of processing nested data structures. – No label assignment.

Approach ODE – Ontology-assisted data extraction PADE wrapper Query result annotation Attribute matching Ontology construction

Approach continued Query result section identification Record segmentation Data value alignment and label assignment – MaxEnt model is used

Experimental Results Extraction performed using DeLa

Conclusion Can only label attributes that appear in query result pages References a few DEG papers – DKE99, Tisp, TANGO Could take advantage of MaxEnt for pre- labeling data Need to look into DeLa for data extraction