ALDA : Cognitive Assistant for Legal Document Analytics

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dc.contributor.authorJoshi, Karuna Pande
dc.contributor.authorGupta, Aditi
dc.contributor.authorMittal, Sudip
dc.contributor.authorPearce, Claudia
dc.contributor.authorJoshi, Anupam
dc.contributor.authorFinin, Tim
dc.date.accessioned2018-11-06T16:41:29Z
dc.date.available2018-11-06T16:41:29Z
dc.date.issued2016-09-18
dc.descriptionAAAI Fall Symposium 2016en_US
dc.description.abstractIn recent times, there has been an exponential growth in digitization of legal documents such as case records, contracts, terms of services, regulations, privacy documents and compliance guidelines. Courts have been digitizing their archived cases and also making it available for e-discovery. On the other hand, businesses are now maintaining large data sets of legal contracts that they have signed with their employees, customers and contractors. Large public sector organizations are often bound by complex legal legislation and statutes. Hence, there is a need of a cognitive assistant to analyze and reason over these legal rules and help people make decisions. Today the process of monitoring an ever increasing dataset of legal contracts and ensuring regulations and compliance is still very manual and labour intensive. This can prove to be a bottleneck in the smooth functioning of an enterprise. Automating these digital workflows is quite hard because the information is available as text documents but it is not represented in a machine understandable way. With the advancements in cognitive assistance technologies, it is now possible to analyze these digitized legal documents efficiently. In this paper, we discuss ALDA, a legal cognitive assistant to analyze digital legal documents. We also present some of the preliminary results we have obtained by analyzing legal documents using techniques such as semantic web, text mining and graph analysis.en_US
dc.description.urihttps://www.aaai.org/ocs/index.php/FSS/FSS16/paper/download/14119/13681en_US
dc.format.extent4 pagesen_US
dc.genreconference papers and proceedings pre-printen_US
dc.identifierdoi:10.13016/M2H70844R
dc.identifier.citationKaruna Pande Joshi, Aditi Gupta, Sudip Mittal, Claudia Pearce, Anupam Joshi, and Tim Finin, ALDA : Cognitive Assistant for Legal Document Analytics, AAAI Fall Symposium 2016, https://www.aaai.org/ocs/index.php/FSS/FSS16/paper/download/14119/13681en_US
dc.identifier.urihttp://hdl.handle.net/11603/11890
dc.language.isoen_USen_US
dc.publisherAssociation for the Advancement of Artificial Intelligenceen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Information Systems Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Student Collection
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.subjectartificial intelligenceen_US
dc.subjectnatural language processingen_US
dc.subjectsemantic weben_US
dc.subjectUMBC Ebiquity Research Groupen_US
dc.titleALDA : Cognitive Assistant for Legal Document Analyticsen_US
dc.typeTexten_US

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