| Abstract |
Semantic Vectorization techniques have proven useful in identifying patterns between documents. These techniques make use of text and context to generate vectors which can then be compared against each other to find similarity. However, current techniques require data to be centrally located. In a coalition scenario this may be impossible, coalition partners may be unwilling or unable to share their data. It becomes necessary to develop a technique that will take advantage of vectorization approaches without moving data from their origin site |
| Authors |
- Dean Steuer (IBM US)
- Shalisa Witherspoon (IBM US)
- Graham Bent (IBM UK)
- Geeth de Mel (IBM UK)
- Dave Braines (IBM UK)
- Roger Whitaker (Cardiff)
- Nirmit Desai (IBM US)
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| Date |
Sep-2020 |
| Venue |
4th Annual Fall Meeting of the DAIS ITA, 2020 |
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| Variants |
- <a href="\doc-XXXX\”>doc-6109</a>
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