Abstract
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.
Original language | English |
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Number of pages | 6 |
Publication status | Published - 8 Jun 2015 |
Event | Workshop on Using Machine Learning and Other Advanced Techniques to Address Legal Problems in E-Discovery and Information Governance (DESI VI Workshop) - San Diego, United States Duration: 8 Jun 2015 → 8 Jun 2015 |
Workshop
Workshop | Workshop on Using Machine Learning and Other Advanced Techniques to Address Legal Problems in E-Discovery and Information Governance (DESI VI Workshop) |
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Abbreviated title | ICAIL 2015 |
Country/Territory | United States |
City | San Diego |
Period | 8/06/15 → 8/06/15 |