Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
AGENTS '98 Proceedings of the second international conference on Autonomous agents
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Text mining: finding nuggets in mountains of textual data
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Modern Information Retrieval
Using an ontology to simplify data access
Communications of the ACM
The SMART Retrieval System—Experiments in Automatic Document Processing
The SMART Retrieval System—Experiments in Automatic Document Processing
On original generation of structure in legal documents
ICAIL '03 Proceedings of the 9th international conference on Artificial intelligence and law
An e-government information architecture for regulation analysis and compliance assistance
ICEC '04 Proceedings of the 6th international conference on Electronic commerce
A relatedness analysis approach for regulation comparison and e-rulemaking applications
dg.o '05 Proceedings of the 2005 national conference on Digital government research
REGBASE: a distributed information infrastructure for regulation management and compliance checking
dg.o '04 Proceedings of the 2004 annual national conference on Digital government research
Legal information retrieval and application to e-rulemaking
ICAIL '05 Proceedings of the 10th international conference on Artificial intelligence and law
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Government regulations are semi-structured text documents that are often voluminous, heavily cross-referenced between provisions and even ambiguous. Multiple sources of regulations lead to difficulties in both understanding and complying with all applicable codes. In this work, we propose a framework for regulation management and similarity analysis. An online repository for legal documents is created with the help of text mining tool, and users can access regulatory documents either through the natural hierarchy of provisions or from a taxonomy generated by knowledge engineers based on concepts. Our similarity analysis core identifies relevant provisions and brings them to the user's attention, and this is performed by utilizing both the hierarchical and referential structures of regulations to provide a better comparison between provisions. Preliminary results show that our system reveals hidden similarities that are not apparent between provisions based on node content comparisons.