Towards Domain-Independent Information Extraction from Web Tables

Towards Domain-Independent Information Extraction from Web Tables

Wolfgang Gatterbauer, Paul Bohunsky, Marcus Herzog,Bernhard Krupl, and Bernhard Pollak

Presented by Aaron StewartBYU CS 652

Table Extraction Using Spatial Reasoning in the CSS2 Visual Box Model

Database and Artificial Inteligence GroupVienna University of Technology, Austria

Wolfgang Gatterbauer and Paul Bohunsky

Contributions

1. Classify visually structured data2. Non-tree IE formalism3. Argue to defer semantic interpretation of

output4. Ground truthing method5. Web table test set6. Visual results

Introduction

Source: Gatterbauer et al. 2007

Visually Structured Data on the Web

• Tables• Lists• Aligned Graphs

Visually Structured Data on the Web

Source: Gatterbauer et al. 2007

Formal Setup

• DOM Tree Representation• Visual Box Representation– Visualized Element Nodes (VENs)• DOM nodes with bounding boxes

– Visualized Words• Text words with bounding boxes

Formal Setup

Source: Gatterbauer et al. 2007

Information Extraction

• Visualized Element Nodes Table extraction (VENTex)

• Steps:– Table location– Table recognition– Table interpretation

Information Extraction

Source: Gatterbauer et al. 2007

Table Extraction

Source: Gatterbauer et al. 2007

Table Extraction

1. Gather 8 HTML node attributes2. For text, add link3. Only accept TH, TD, DIV html nodes4. Tables must form frames5. Remove duplicate bounding boxes

Table Extraction

6. Adjacency: 3 pixels7. LOCATEFRAMES algorithm8. No overlapping cells9. Minimum 3 rows, 2 columns10. Remove empty rows/columns (spacers)

LOCATE FRAMES Algorithm (earlier paper)

• Visual table model• Expansion algorithm

Visual Table Model

Source: Gatterbauer et al. 2007

Double Topographical Grid???

• Two origins– Upper left corner– Lower right corner

• Sorted lists of pixel positions– The numbers are indices– But pixels remain in regular coordinates

Neighbor Relations

Source: Gatterbauer et al. 2007

Neighbor Relations

• Expand to include neighbors 1,2,3,4– within or equal – Not bigger– Not outside– Not stepped

Expansion Algorithm

Source: Gatterbauer et al. 2007

Basic Algorithm

• http://www.dbai.tuwien.ac.at/staff/gatter/work/AAAI_2006_Presentation_Table_Extraction_Spatial_Reasoning.pdf

Table Interpretation

• Argument– Few details about the method actually used– Take data as it comes– Pass it on to a later semantic processing stage

Table Interpretation

Source: Gatterbauer et al. 2007

Performance

• Load + render: O(n)• Double topographical grid: O(n sqrt(n))• About 5 seconds per page

Web Table Ground Truthing

• Tool to copy web pages– (not easy!)– http://

www.dbai.tuwien.ac.at/user/pollak/webpagedump

• Students selected and submitted pages– 493 web tables– 269 web pages– 63 students– http://www.dbai.tuwien.ac.at/staff/gatter/ventex/

Experimental Results

Source: Gatterbauer et al. 2007

Future Work• Table extraction• Table interpretation• Nested substructures• Other visually structured data• Information integration

Source: Gatterbauer et al. 2007

My Conclusions

• Useful table-building algorithm– For electronic data only– Requires strict alignment

• Could be expanded– Other electronic formats (PDF, even ASCII text)– Probabilistic model for jitter