Measuring Similarity Between Contexts and Concepts
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An invited talk from 2005 about measuring similarity of raw text and concepts.
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Measuring Similarity Between Contexts and Concepts
- 1. Measuring Similarity Between Concepts and Contexts Ted Pedersen Department of Computer Science University of Minnesota, Duluth http://www.d.umn.edu/~tpederse
- 30. Limits of co-occurrence vectors 0 52.27 0 0.92 0 4.21 0 28.72 0 3.24 0 1.28 0 2.53 Weapon Missile Shoot Fire Destroy Murder Kill 17.77 0 14.6 46.2 22.1 0 34.2 19.23 2.36 0 72.7 0 1.28 2.56 Execute Command Bomb Pipe Fire CD Burn
- 34. Name Conflated Data 51.4% 231,069 JapAnce 112,357 France 118,712 Japan 53.9% 46,431 JorGypt 21,762 Egyptian 25,539 Jordan 56.0% 13,734 MonSlo 6,176 Slobodan Milosovic 7,846 Shimon Peres 58.6% 5,807 MSIIBM 2,406 IBM 3,401 Microsoft 73.7% 4,073 JikRol 1,071 Rolf Ekeus 3,002 Tajik 69.3% 2,452 RoBeck 740 David Beckham 1,652 Ronaldo Maj. Total New Count Name Count Name
- 35. 50.3 50.3 51.1 51.1 51.4 231,069 JapAnce 53.0 57.0 59.1 56.6 53.9 46,431 JorGypt 91.4 54.6 96.6 62.8 56.0 13,734 MonSLo 60.0 68.0 51.3 47.7 58.6 5,807 MSIIBM 90.4 91.0 96.2 94.7 73.7 4,073 JikRol 54.7 85.9 72.7 57.3 69.3 2,452 Robeck Ft 20 Ft 5 Ft 20 Ft 5 Maj. # Cxt 20 Cxt 5