Aaai 2006 Pedersen
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Aaai 2006 Pedersen
- 1. Language Independent Methods of Clustering Similar Contexts (with applications) Ted Pedersen University of Minnesota, Duluth [email_address] http:// www.d.umn.edu/~tpederse/SCTutorial.html
- 19. Identifying Lexical Features Measures of Association and Tests of Significance
- 28. 2x2 Contingency Table 100,000 99,700 300 99,600 99,400.0 99,301.2 200.0 298.8 !Artificial 400 300.0 398.8 100.0 000.12 Artificial !Intelligence Intelligence
- 34. Context Representations First and Second Order Methods
- 39. First Order Vectors of Unigrams 1 0 1 0 1 Cxt4 0 0 0 0 0 Cxt3 1 1 0 1 0 Cxt2 1 1 1 1 1 Cxt1 child magic curse black island
- 41. First Order Vectors of Bigrams 1 0 1 1 0 Cxt4 0 1 1 0 0 Cxt3 1 0 0 0 1 Cxt2 1 0 0 1 1 Cxt1 voodoo child serious error military might island curse black magic
- 45. Word by Word Matrix 120.0 0 69.4 0 0 voodoo 0 89.2 0 21.2 0 serious 0 54.9 100.3 0 0 military 73.2 0 0 189.2 0 island 43.2 0 0 0 123.5 black child error might curse magic
- 47. There was an island curse of black magic cast by that voodoo child. 120.0 0 69.4 0 0 voodoo 73.2 0 0 189.2 0 island 43.2 0 0 0 123.5 black child error might curse magic
- 50. There was an island curse of black magic cast by that voodoo child. 78.8 0 24.4 63.1 41.2 Cxt1 child error might curse magic
- 54. Dimensionality Reduction Singular Value Decomposition
- 58. Word by Word Matrix 4 2 0 0 0 3 0 1 box 0 1 2 2 1 2 0 0 memory 0 0 0 1 0 0 2 0 organ 0 2 0 3 2 0 0 0 debt 0 1 0 3 1 0 0 2 linux 0 1 0 3 2 0 0 0 sales 3 0 2 2 0 3 0 0 lab 1 0 2 0 0 1 2 0 petri 0 1 0 0 2 0 0 1 disk 1 0 2 0 0 0 3 0 body 0 0 0 3 1 0 0 2 pc plasma graphics tissue data ibm cells blood apple
- 59. Singular Value Decomposition A=UDV’
- 60. Word by Word Matrix After SVD 1.1 1.0 .98 1.7 .86 .72 .85 .77 memory .00 .00 .17 1.2 .77 .00 .84 .00 organ .00 1.5 .00 3.2 2.1 .00 .00 1.2 debt .13 1.1 .03 2.7 1.7 .16 .00 .96 linux .41 .85 .35 2.2 1.3 .39 .15 .73 sales 2.3 .18 2.5 1.7 .35 2.0 1.7 .21 lab 1.4 .00 1.5 .49 .00 1.2 1.1 .00 germ .00 .91 .00 2.1 1.3 .01 .00 .76 disk 1.5 .00 1.6 .33 .00 1.3 1.2 .00 body .09 .86 .01 2.0 1.3 .11 .00 .73 pc plasma graphics tissue data ibm cells blood apple
- 63. Feature by Context Representation 0 1 0 0 serious error 1 0 1 1 voodoo child 0 1 0 0 military might 1 0 0 1 island curse 1 0 1 1 black magic Cxt4 Cxt3 Cxt2 Cxt1
- 65. Clustering Partitional Methods Cluster Stopping Cluster Labeling
- 72. Contexts to be Clustered
- 73. Ball of String (I1 Internal Criterion Function)
- 74. Flower (I2 Internal Criterion Function)
- 76. The Fan (E1 External Criterion Function)
- 78. Cluster Stopping
- 81. H2 versus k T. Blair – V. Putin – S. Hussein
- 83. PK2 predicts 3 senses T. Blair – V. Putin – S. Hussein
- 85. PK3 predicts 3 senses T. Blair – V. Putin – S. Hussein
- 87. Cluster Labeling
- 91. Evaluation Techniques Comparison to gold standard data