ASAIL 2017
Automated Semantic Analysis of Information in Legal Text

Table of Contents

• Preface
  
  

Session 1: Rule Parsing, Text Classification, Segmentation

• Semi-automated creation of regulation rule bases using generic template-driven rule extraction
  Deepali Kholkar , Sagar Sunkle , Vinay Kulkarni
• Automating Judicial Document Analysis
  L. Karl Branting

Session 2: Neural Models and Corpora

• Solving Bar Exam Questions with Deep Neural Networks
  Adebayo Kolawole John , Luigi Di Caro , Guido Boella
• BO-ECLI Parser Engine: the Extensible European Solution for the Automatic Extraction of Legal Links
  Tommaso Agnoloni , Lorenzo Bacci , Marc van Opijnen
• Exploring the Use of Text Classification in the Legal Domain
  Octavia-Maria Şulea , Marcos Zampieri , Shervin Malmasi , Mihaela Vela , Liviu P. Dinu , Josef van Genabith

Session 3: Word Embeddings and Topic Models

• Extending Thesauri Using Word Embeddings and the Intersection Method
  Jörg Landthaler , Bernhard Waltl , Dominik Huth , Daniel Braun , Christoph Stocker , Thomas Geiger , Florian Matthes
• An Analysis of Topic Modelling for Legislative Texts
  James O’ Neill , Cécile Robin , Leona O’ Brien , Paul Buitelaar

Session 4: Semantics and Default Logic

• Semantic Types for Decomposing Evidence Assessment in Decisions on Veterans’ Disability Claims for PTSD
  Vern R. Walker , Ashtyn Hemendinger , Nneka Okpara , Tauseef Ahmed
• Towards Formalizing Statute Law as Default Logic through Automatic Semantic Parsing
  Marcos Pertierra , Sarah Lawsky , Erik Hemberg , Una-May O’Reilly