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Nomatic*IM

Nomatic*IM for presence Position-to-place problem At the campus Starbucks, I’m… reading drinking coffee drinking a Frappacino/latte/etc. doing homework at Starbucks at a coffee shop at UCI in Orange County in Irvine in the U.S. drinking coffee At Starbucks, drinking a Frappacino

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Nomatic*IM

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  1. Nomatic*IM • for presence

  2. Position-to-place problem

  3. At the campus Starbucks, I’m… • reading • drinking coffee • drinking a Frappacino/latte/etc. • doing homework • at Starbucks • at a coffee shop • at UCI • in Orange County • in Irvine • in the U.S.

  4. drinking coffee At Starbucks, drinking a Frappacino at starbucks drinking coffee drinking coffee la la la la at starbucks having coffee at a café reading starbucks, drinking a delicious caramel frappacino with bill and george at a coffee shop doing homework

  5. Nomatic*IM

  6. How • Gather sensor data. • Running applications, time of day, local wireless access points, connected displays, etc. • Build decision trees from that data. • Collect the data.

  7. Why • We get situated labels. • We get labels broadly. • People will use it. • Privacy is possible.

  8. Future • User studies. • Release (pending IRB approval). • Make it better.

  9. Sam Kaufman kaufmans@uci.edu Donald J. Patterson djp3@ics.uci.edu Department of Informatics Bren School of Information and Computer Sciences University of California, Irvine

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