REGBASE

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REGNET
Legal Information Retrieval and Application to
E-Rulemaking
Gloria Lau, Kincho Law, Gio Wiederhold June 8th,
2004
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Motivation

• Multiple sources of regulations
• Multiple jurisdictions federal, state, local,
  etc.
• Different formats, terminologies, contexts

• Amending rules, conflicting ideas

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Motivation

• Multiple sources of regulations
• Multiple jurisdictions federal, state, local,
  etc.
• Different formats, terminologies, contexts
• Amending rules, conflicting ideas
• ? Need for a repository
• Locate relevant information
• E.g., small business penalty fees for violations
• ? Need for analysis tool
• Complexity of regulations
• Multiple jurisdictions
• Understanding of regulations their
  relationships

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Example 1 Related Provisions

• ADAAG Appendix 4.6.3
• Such a curb ramp opening must be located
  within the access aisle boundaries, not within
  the parking space boundaries.
• CBC 1129B.4.3
• Ramps shall not encroach into any parking
  space.
• Exception 1. Ramps located at the front of
  accessible parking spaces may encroach into the
  length of such spaces
• CBC allows curb ramps encroaching into accessible
  parking stall access aisles, while ADA disallows
  encroachment into any portion of the stall.

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Example 2 Related but Conflicting Provisions

• ADAAG 4.7.2
• Slope. Transitions from ramps to walks,
  gutters, or streets shall be flush and free of
  abrupt changes
• CBC 1127B.5.5
• Beveled lip. The lower end of each curb ramp
  shall have a ½ inch (13mm) lip beveled at 45
  degrees as a detectable way-finding edge for
  persons with visual impairments.
• ADAAG focuses on wheelchair traversal CBC
  focuses on the visually impaired when using a
  cane.

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Scope

• Repository development
• Relatedness analysis
• Performance evaluation , results and applications

Relatedness analysis
Repository development
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Repository development
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Sources of data

• Accessibility standards
• Americans with Disabilities Act Accessibility
  Guide (ADAAG)
• Drafted chapter for rights-of-way access
• Associated public comments
• Uniform Federal Accessibility Standards (UFAS)
• British Standard BS 8300
• Scottish Technical Standards, Part S
• International Building Code (IBC), Chapter 11
• Drinking water standards
• Code of Federal Regulations, Title 40 (40 CFR)
• California Code of Regulations, Title 22 (22 CCR)
• Fire code
• International Building Code (IBC), Chapter 9

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Computational properties of regulations

• Hierarchical tree structure
• Referential structure
• Discipline-centered, e.g., ADAAG for
  accessibility
• ? Shallow parser to capture computational
  properties

ltregulation id"ibc" name"international building
code" type"private"gt ltregElement id"ibc.1107"
name"special occupancies"gt ltregElement
id"ibc.1107.2" nameassembly area seating"gt
ltreference id"ibc.1107.2.4.1" times"1" /gt
ltconcept name"assembl area" times"1" /gt
ltregTextgtAssembly areas with fixed seating
shall comply lt/regTextgt ltregElement
id"ibc.1107.2.1" name"services"gt...lt/regElementgt
ltregElement id"ibc.1107.2.2"
namewheelchair "gt...lt/regElementgt
lt/regElementgt lt/regElementgt lt/regulationgt
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Scope

• Repository development
• Relatedness analysis
• Performance evaluation , results and applications

Relatedness analysis
Repository development
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Relatedness analysis
Related elements door and entrance

• ADAAG
• 4.1.6(3)(d) Doors
• (i) Where it is technically infeasible to comply
  with clear opening width requirements of 4.13.5,
  a projection ...
•  
• UFAS
• 4.14.1 Minimum Number
• Entrances required to be accessible by 4.1 shall
  be part of an accessible route and shall comply
  with ...

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Relatedness analysis

• To utilize the computational properties of
  regulations for a complete comparison
• Measure
• Degree of relatedness similarity score f(A, U) ?
  (0, 1)
• Nodes A and U are provisions from two different
  regulation trees

f ? (0, 1)
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Base score f0 computation

• Linear combination of feature matching
• F(A,U,i) similarity score between Sections
  (A,U) based on feature i
• N total number of features
• ? weighting coefficient

• Feature matching
• Based on the Vector model using cosine similarity
  as the distance between feature vectors
• Non-Boolean features
• A measurement of 2 inches max can be a 70
  match to 2 inches
• Synonyms exist, e.g., ontology defined for
  chemicals
• Perform vector-space transformation prior to
  cosine computation

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Score refinements based on regulation structure

• Neighbor inclusion
• Diffusion of similarity between clusters of nodes
  in the tree

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Score refinements based on regulation structure

• Reference distribution
• Diffusion of similarity between referencing nodes
  and referenced nodes in the tree
• E.g., f(A5.3, U6.4(a)) updates f(A2.1, U3.3)

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Scope

• Repository development
• Relatedness analysis
• Performance evaluation, results and applications

Relatedness analysis
Repository development
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Performance evaluation

• Conduct a user survey of rankings of similarity
• 10 randomly chosen sections from the ADAAG and
  UFAS
• Ranks 1 to 100 in the order of relevance
• Root mean square error (RMSE)
• user-generated ranking vector
• machine-predicted ranking vector

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Survey results - Tabulated RMSEs

• Compared our analysis to Latent Semantic Indexing
  (LSI)
• ? structural weighting coefficient
• ? feature weighting coefficient
• Average RMSE smaller than LSI
• Measurement feature performs best
• No improvement in result observed for structural
  comparison

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Results of comparisons ADAAG vs. UFAS

• Related accessible elements door and entrance
• Neighbor inclusion reveals higher similarity

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Results of comparisons UFAS vs. BS8300

• Terminological differences - revealed through
  neighbor inclusion

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Results of comparisons UFAS vs. Scottish
Technical Standards

• Terminological differences - revealed through
  reference distribution
• Stairs and ramps

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Application e-rulemaking

• Application domain e-rulemaking
• Comparison between draft of rules and the
  associated public comments
• ADAAG Chapter 11, rights-of-way draft
• Less than 15 pages
• Over 1400 public comments received within 4
  months
• Comments 10MB in size most are several pages
  long
• ? New regulation draft can easily generate a huge
  amount of data that needs to be reviewed and
  analyzed
• Parsing of the draft and comments
• From HTML to XML
• Recreate structure of the draft using our shallow
  parser
• Extract features from the draft and comments
• Treat individual comments as provisions

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E-rulemaking
Drafted regulations compared with public comments
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Results from e-rulemaking application

• Related section in draft and public comment

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Results from e-rulemaking application

• No related provisions identified
• Concern not addressed in the draft

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Conclusions

• A framework for regulatory repository
• Structure of regulations recreated in XML
• Feature extractions
• Prototype for similarity comparisons
• Contextual comparisons
• Domain knowledge
• Structural comparisons
• Performance Evaluation, Results and Applications
• User survey and comparisons with LSI
• Observations of comparisons between Federal,
  State, non-profit organization mandated codes and
  European standards
• Application on e-rulemaking

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Future research directions

• In the legal domain
• Regulatory competition
• Cross border data transfer laws
• Especially in the polyglot countries in EU
• Regulatory updates
• Track changes in updates
• Track cross references between regulations
• Extension of application to other domains of
  semi-structured documents
• Software specifications
• User manuals
• Similarity/relatedness is settled - how about
  differences and conflicts?
• A lot of almost identical provisions

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Thank You!