A relatedness analysis of government regulations using domain knowledge and structural organization

The complexity and diversity of government regulations make understanding and retrieval of regulations a non-trivial task. One of the issues is the existence of multiple sources of regulations and interpretive guides with differences in format, terminology and context. This paper describes a comparative analysis scheme developed to help retrieval of related provisions from different regulatory documents. Specifically, the goal is to identify the most strongly related provisions between regulations. The relatedness analysis makes use of not only traditional term match but also a combination of feature matches, and not only content comparison but also structural analysis. Regulations are first compared based on conceptual information as well as domain knowledge through feature matching. Regulations also possess specific organizational structures, such as a tree hierarchy of provisions and heavy referencing between provisions. These structures represent useful information in locating rel...

• Type: Journal
• Year: 2006
• Where: IR
• Authors: Gloria T. Lau, Kincho H. Law, Gio Wiederhold
• Keywords: IR 2006, Natural Language Processing, Related Provisions, Relatedness Analysis, Structural Analysis