Formalizing and Querying Heterogeneous Documents with Tables Krishnaprasad Thirunarayan and Trivikram Immaneni Department of Computer Science and Engineering Wright State University Dayton, OH-45435

Overall R&D Agenda Develop semi-automatic techniques for information extraction/retrieval to enable man and machine to complement each other in assimilation of semi-structured, heterogeneous documents => Semantic Web Technologies.

Goal (What?) Background and Motivation (Why?) Implementation Details (How?) Evaluation and Applications (Why?) Conclusions

Goal

Define, embed, and use metadata in semi- structured documents containing tables. Content-oriented/domain-specific annotation of human sensible document Makes explicit semantics of complex data Enables augmentation of an interpretation in a modular fashion.

Heterogeneous Document

Background and Motivation

Generate XML Master Document that is both machine processable and that can serve as a basis for human sensible presentation. Basis of semi-automation in practice.

Embedding metadata improves traceability, thereby facilitating Content Extraction Verification Update

Implementation Details (How?)

XML Technology Document-Centric View: XML is used to annotate documents for use by humans in the realm of document processing and content extraction. Data-Centric View: XML is used as text- based format for information exchange / serialization in the context of Web Services.

Basic idea behind our approach Unify the two views by using XML- elements to materialize abstract syntax, and together with XML attributes and XML element definitions, formalize the content.  Key advantage: Minimizes maintenance of additional data structures to relate original document with its formalization.

Two Concrete Implementations Use Web Services language Water which amalgamates XML Technology with programming language concepts Use XML/XSLT infrastructure

Water-based approach Each annotation reflects the semantics of the text fragment it encloses. The annotated data can be interpreted by viewing it as a function/procedure call in Water. The correspondence between formal parameter and actual argument is position-based. The semantics of annotation is defined in Water as a method definition in a class, separately.

Example Table Thickness (mm) Tensile Strength (ksi) Yield Strength (ksi) 0.50 and under – –

Example of Tagged Table Thickness (mm) Tensile Strength (ksi) Yield Strength (ksi) table and under table table table....

Example of Processing Code /> <set rows= table.rows. />/> …

XML/XSLT-based approach Each annotation reflects the semantics of the text fragment it encloses. To make the annotated data XML compliant, dummy attributes such as one, two, three, … etc are introduced. The correspondence between formal attribute and the actual value is name-based. The semantics is defined modularly by interpreting XML- elements and its XML-attributes via XSLT, separately.

Example of Tagged Table <tableSchema one="Thickness(min)" two="Thickness(max)" three="Tensile Strength“ four="Yield Strength"/>...

XSLT Stylesheets can be used to: Query: to perform table look-ups. Transform: to change units of measure such as from standard SI units to FPS units and vice versa. Format: to display the table in HTML form. Extract: to recover the original table. Verify: to check static semantic constraints on table data values.

Evaluation and Application (Why?)

Advantage Only tabular data in each document is annotated. The annotation definition is factored out as background knowledge. Thus, the semantics of each table type is specified just once outside the document and is reused with different documents containing similar tables.

Disadvantage Both avenues require mature tool support for wide spread adoption. For example, develop MS FrontPage like interface where the Master document is the annotated form, and the user explicitly interacts with/edits only a view of the annotated document, for readability reasons, and has support for export as XML to generate well-formed XML document.

Prolog rendition strengthTableRow( 0, 0.50, 165, 155). strengthTableRow(0.50, 1.00, 160, 150). strengthTableRow(1.00, 1.50, 155, 145).... strengthTable(Thickness, TensileStrength, YieldStrength) :- strengthTableRow(L, U, TensileStrength, YieldStrength), L = Thickness. thicknessToTensileStrength(Thickness, TensileStrength) :- strengthTable(Thickness, TensileStrength, _). thicknessToYieldStrength(Thickness, YieldStrength) :- strengthTable(Thickness, _, YieldStrength). ?- thicknessToYieldStrength(0.6,YS).

Conclusion and Future Work

Develop a catalog of predefined tables, specifying them using Semantic Web formalisms (such as RDF, OWL, etc) and mapping the tabular data into a set of pre- defined tables, possibly qualified. Develop techniques for manual mapping of complex tables into simpler ones: To provide semantics to data. To improve traceability. To facilitate automatic manipulation.

Tailor and improve IE and IR techniques developed in the context of text processing to Semantic Web documents such as in XML, RDF, etc benefiting from additional support from ontologies such as in OWL, etc

Holy Grail Ultimately develop principles, techniques and tools, to author and extract human-readable and machine-comprehensible parts of a document hand in hand, and keep them side by side.