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Semantic Search in E-Discovery

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Semantic Search in E-Discovery

  1. 1. Semantic Search in E-DiscoveryResearch on the application of text mining and information retrievalfor fact finding in regulatory investigations David Graus
  2. 2. Who’s Involved? Prof. dr. Maarten de Rijke Dr. Hans Henseler Lector E-Discovery, CREATE-IT applied Director Intelligent Systems Lab, UvA research David Graus, MSc. David van Dijk, MSc. PhD Candidate, Semantic Search Researcher E-Discovery, CREATE-IT applied research in E-Discovery, UvA Zhaochun Ren, MSc. Menno Israël, MSc. Teamleader Knowledge and Expertise PhD Candidate, Semantic Search Centre for Intelligent Data Analysis in E-Discovery, UvA (Kecida), NFI Semantic search in e-discovery 2
  3. 3. Introduction £ Semantic Search in E-Discovery Semantic search in e-discovery 3
  4. 4. What is £ Semantic Search in E-Discovery ˜ retrieving and securing digital forensic evidence Semantic search in e-discovery 4
  5. 5. What is £ Semantic Search in E-Discovery Semantic search in e-discovery 5
  6. 6. What is £ Semantic Search in E-Discovery ˜ retrieving and securing digital forensic evidence ˜ from emails, forums, etc... Semantic search in e-discovery 6
  7. 7. What is £ Semantic Search in e-Discovery Semantic search in e-discovery 7
  8. 8. Challenge¢ Finding out who knew what, from whom, and when Semantic search in e-discovery 8
  9. 9. Challenge¢ Finding out who knew what, from whom, and when¢ Generic search is not the answer Semantic search in e-discovery 9
  10. 10. Finding evidence for E-Discovery¢ We don’t know what we’re looking for¢ What we’re looking for might be deliberately hidden¢ Communication might be very domain-specific, contextualized or incomplete Semantic search in e-discovery 10
  11. 11. Task¢ Retrieve all relevant traces¢ Highly iterative search process¢ Support (re)formulating questions and hypotheses Semantic search in e-discovery 11
  12. 12. How do we approach this?¢ Two subprojects: £ Information Retrieval ˜ Finding material of unstructured nature from large collections £ Information Extraction/Text Mining ˜ Discovering patterns in data Semantic search in e-discovery 12
  13. 13. How do we approach this?¢ Information Retrieval £ Integrating structure/context of data in retrieval models ˜ Capturing forum and email context ˜ Conversational search Semantic search in e-discovery 13
  14. 14. How do we approach this?¢ Information Extraction/Text Mining £ Extracting structured knowledge from user generated content ˜ Semantic pre-processing ˜ Social network inference ˜ Information maps Semantic search in e-discovery 14
  15. 15. How do we approach this?¢ Information Retrieval <-> Information Extraction Semantic search in e-discovery 15
  16. 16. Current work (first steps)¢ Information Retrieval £ Twitter Mining (as a form of conversational search)¢ Information Extraction/Text Mining £ Entity linking (for semantic document enrichment)¢ TREC/TAC benchmarking events £ TREC Legal Track 2011 (2013?) Semantic search in e-discovery 16
  17. 17. Contributions¢ xTAS: Open source text analysis toolkit¢ iColumbo: Internet monitoring framework¢ Used by: £ Internet Recherche Netwerk £ Koninklijke Bibliotheek £ Beeld en Geluid £ ... You? Semantic search in e-discovery 17
  18. 18. Semantic search in E-discovery¢ David Graus¢ d.p.graus@uva.nl Semantic search in e-discovery 18

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