Understanding Web Query Interfaces: Best-Efforts Parsing with Hidden Syntax

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Understanding Web Query Interfaces Best-Efforts
Parsing with Hidden Syntax

• Zhen Zhang, Bin He and Kevin C. Chang

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MetaQuerier Goals Exploring and integrating the
deep Web
FIND sources
QUERY sources

• Integrator
• source selection
• schema integration
• query mediation

• Explorer
• source discovery
• source modeling
• source indexing

Cars.com
Amazon.com
411localte.com
Apartments.com
The Deep Web Databases on the Web
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Problem Source capability extraction Or, query
interface understanding.
Book sources
Music sources
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Form understanding What are the essential tasks?

• Output all the conditions, for each
• Grouping elements (into query conditions)
• Tagging elements with their semantic roles

attribute
operator
value
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Demo summary
Query form
Understanding form structure
Multiple interpretations
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Certainly not a trivial task - Recall the
butterfly ballot in U.S. Election 2000.
Even just grouping can be hard!
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Baseline approach? The problem seems to be rather
heuristic in nature

• There seem to be no clear criteria, but only
  fuzzy heuristics
• Grouping is hard it is often n-ary
• Heuristic Group two elements if they are close
• But
• Tagging is hard no semantic labeling in HTML
  forms
• Heuristic Tag the closest text as the
  attribute
• But
• We need many such heuristics!
• Goal A principled mechanism to encode and use
  the various heuristics systematically?

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Our observation concerted structures of QI

• Condition pattern as building blocks
• Convergence condition patterns

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Our insight Cope with form complexity by their
composition patterns.

• Lego-like building blocks
• Pattern of elements composed into conditions
• Pattern of conditions composed into a form
• So, how to realize our divide-and-conquer idea?
  Any computation paradigm?

Source
Q-Form
Lego Building Blocks
?
Semantic Structure
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Our Hypothesis Existence of Hidden-Syntax

• Query-form creation is guided by hidden syntax

Semantic Structure (Query Conditions)
Presentation (Query Interface)
Attr title Operator title words,. Value
string
Parsing is thus a principled mechanism for the
inverse
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This language paradigm enables principled
solution to a seemingly heuristic problem

• Essential notions Grammar and Parser
• Grammar Pattern specification
• Declarative
• No need to hard-code heuristics
• Collective
• Capture both micro and macro patterns
• Parser Pattern recognition
• Global
• Coherently interpret an entire query form
• Systematic
• Systematically assembles the building blocks

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However, the hidden-syntax hypothesis itself
entails challenges in its realization

• Hidden syntax is only hypothetical
• We must derive a grammar in its place
• What should be captured in a derived grammar?
• 2P-Grammar Production Preference
• productions for patterns preferences for their
  precedence
• Derived grammar is secondary to any input
• Inherently incomplete and ambiguous
• What should be the machinery of a soft parser?
• Best-effort Parser
• multiple, maximal-partial parse trees

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Our Paradigm Best-Effort Visual Language
Parsing Framework
Input HTML query form
2P Grammar
Preferences
Productions
BE-Parser
Ambiguity Resolution Error Handling
X
Output semantic structure
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Grammar Layout based
Traditional grammar (Sequential based 1-D)
Our grammar (Layout based 2-D)
Presentation
3 5
TextCond - left(TextAttr, TextVal) Ú
above(TextAttr, TextVal) Ù above(TextVal,
TextOp)
E - E E, or E - sequential(E, , E)
Grammar
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Parser Logic programming style

• Traditional parsing
• Scan input sequentially
• Our parsing
• Nonlinear input
• Arbitrary constraints

Parse trees
. . .
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Thats not all complications of hypothetical
syntax

• Hidden syntax is only hypothetical !

Ambiguous
Incomplete
Grammar
Parser
Multiple parse trees
Partial parse trees
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Ambiguity
TextCond Below(Attr,Selection)

• Grammar
• Preferences to capture the conventional
  precedence
• eg. RButton TextCond
• Parser
• Just-in-time pruning by preference
• Multiple trees possible

RButton Left(radio,text))
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Incompleteness

• Grammar
• Cannot capture all patterns
• Parser
• Cannot interpret entire query interfaces
• Interpret as much as possible
• Greedily choose the maximum parse trees
• Reasoning they look at big picture and consider
  more context

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Error Handling Best-effort parser can output
multiple and partial parse trees

• Union all the conditions interpreted by all the
  parse trees.
• Report both conflicts and missing errors

Parsing
Union
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Experiment How a global grammar will do?

• Global grammar
• Derived from Basic captures 21 patterns
• 82 productions, 39 non-terminals, 16 terminals
• Datasets
• Basic 3 domains (Airfare, Autos, Books) 150
  sources
• NewSource same domains, 30 sources
• NewDomain 6 new domains (Music, ), 42 sources
• Random 30 sources (from invisible-web.net)

• Correctness judgment
• Number of correctly identified (grouping and
  tagging) conditions

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Conclusion Syntactic Parsing for Interface
Understanding

• Query interface understanding by syntactic
  parsing with hidden grammars
• Insight
• Exploit how semantics connects to presentation,
  in a syntactic way
• Future work
• Constructing grammar automatically
• Developing more sophisticated preference
  framework
• Extending the framework to other applications

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Thank you !

• For more information
• Online demo at MetaQuerier project Web site
• http//metaquerier.cs.uiuc.edu
• Invite you to our MetaQuerier demo in the
  afternoon