UMBC ebiquity

ALDA: Automated Legal Document Analytics

Status: Active project

Project Description:

There has been an exponential growth in use of digitized legal documents in recent years. Majority of services on the Internet have associated legal documents such as Terms of Services, Privacy Policies and Service Level agreements. A large corpus of court cases, judgments and compliance/regulations are now digitally available for e-discovery. Moreover, businesses are maintaining large data sets of legal contracts that they have signed with their employees, customers and contractors. Furthermore, companies have to adhere to a variety of compliance and regulatory policies for many of these contracts, which are also increasingly digitally available. Managing and monitoring an ever increasing dataset of legal contracts, regulations and compliance is still a very manual and labour intensive job and can be a bottleneck in the smooth functioning of the enterprise.

Our research aims at building a Legal Question and Answer (LQnA) system that will be built upon large scale document analytics of legal documents using various techniques from deep learning, machine learning, natural language processing and text mining. We are working to transform legal databases from textual databases to graph-based datasets using Semantic Web technologies. Our long term goal is to develop a system that for any given action or question, can highlight all the statutes, laws and case law that might be applicable on it and offer preliminary guidance to a counsel. As a shorter term vision, we're looking to see if we can automatically extract elements from compliance and regulatory legal documents that govern Information Technology (IT) outsourcing/cloud computing and automatically monitor for compliance.

Start Date: June 2014

End Date: June 2018

Principal Investigator:
Karuna Pande Joshi

Affiliated Faculty:
Tim Finin
Aditi Gupta
Anupam Joshi

Students:
Sudip Mittal

Collaborators:
Claudia Pearce

Tags: cloud computing, sla, text mining, automatic sla monitoring

 

There are 7 associated publications:  Hide the list...

7 Refereed Publications

2016

1. Karuna Pande Joshi et al., "Semantic Approach to Automating Management of Big Data Privacy Policies", InProceedings, IEEE BigData 2016, December 2016, 373 downloads.

2. Karuna Pande Joshi et al., "ALDA : Cognitive Assistant for Legal Document Analytics", InProceedings, AAAI Fall Symposium 2016, September 2016, 270 downloads.

3. Aditi Gupta et al., "Streamlining Management of Multiple Cloud Services", InProceedings, IEEE International Conference on Cloud Computing, June 2016, 322 downloads.

4. Sudip Mittal et al., "Automatic Extraction of Metrics from SLAs for Cloud Service Management", InProceedings, 2016 IEEE International Conference on Cloud Engineering (IC2E 2016), April 2016, 353 downloads.

2015

5. Sudip Mittal et al., "Parallelizing Natural Language Techniques for Knowledge Extraction from Cloud Service Level Agreements", InProceedings, 2015 IEEE International Conference on Big Data, October 2015, 343 downloads.

6. Karuna Pande Joshi et al., "Automating Cloud Service Level Agreements using Semantic Technologies", InProceedings, CLaw Workshop, IEEE International Conference on Cloud Engineering (IC2E), March 2015, 451 downloads.

2014

7. Karuna Pande Joshi et al., "Automating Cloud Services Lifecycle through Semantic technologies", Article, IEEE Transactions on Service Computing, January 2014, 1110 downloads.

 

There is 1 associated resource:  Hide the list...

1. Ontology for Data Privacy Policy, Ontology.

 

Research Areas:
 Cloud computing
 Knowledge Representation and Reasoning
 Machine learning
 Question and Answering (QnA) System
 Security, Trust and Privacy
 Semantic Web
 Web based information systems
 Web services

 

Assertions:

  1. (Project) ALDA: Automated Legal Document Analytics has principal investigator (Person) Karuna Pande Joshi