||Who is Involved? Semantic Search for E-Discovery
||David van Dijk, David Graus, Zhaochun Ren, Hans Henseler, Maarten de Rijke
||DESI VI: Workshop on Using Machine Learning and Other Advanced Techniques to Address Legal Problems in E-Discovery and Information Governance
||ICAIL ’15: The 15th International Conference on Artificial Intelligence & Law
||San Diego, United States of America
||E-discovery projects typically start with an assessment of the collected electronic data in order to estimate the risk to prosecute or defend a legal case. This is not a review task but is appropriately called early case assessment, which is better known as exploratory search in the information retrieval community. This paper first describes text mining methodologies that can be used for enhancing exploratory search. Based on these ideas we present a semantic search dashboard that includes entities that are relevant to investigators such as who knew who, what, where and when. We describe how this dashboard can be powered by results from our ongoing research in the “Semantic Search for E-Discovery” project on topic detection and clustering, semantic enrichment of user profiles, email recipient recommendation, expert finding and identity extraction from digital forensic evidence.
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