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0.08
1.0E-03
0.6
6.0E-02
0.12
9.0E-04
0.07
0.5
5.0E-02
0.1
8.0E-04
0.06
7.0E-04
0.4
4.0E-02
0.08
0.05
R6R21-V
R6R21-C
R20-V
R20-C
6.0E-04
R50-V
R50-C
R10R32-V
R10R32-C
R58-V
R58-C
R41R79-V
R41R79-C
0.04
5.0E-04
0.3
3.0E-02
0.06
4.0E-04
0.03
0.2
2.0E-02
0.04
3.0E-04
0.02
2.0E-04
0.1
1.0E-02
0.02
0.01
1.0E-04
0
0.0E+00
0
0.0E+00
0
50
70
90
110
130
150
50
70
90
110
130
150
50
70
90
110
130
150
a) number of documents
b) number of documents
c) number of documents
Fig. 3. Learning a third topic of interest: a) n. 1b) n. 2c) n. 3d) n. 4e) n. 5f) n. 6
0.08
5.0E-04
0.6
0.002
0.18
4.5E-04
0.0018
0.07
0.16
0.5
4.0E-04
0.0016
0.14
0.06
3.5E-04
0.0014
0.4
0.12
0.05
3.0E-04
R6R21-V
R6R21-C
R20-V
R20-C
0.0012
R50-V
R50-C
R10R32-V
R10R32-C
R58-V
R58-C
R41R79-V
R41R79-C
0.1
0.04
2.5E-04
0.3
0.001
0.08
2.0E-04
0.0008
0.03
0.2
0.06
1.5E-04
0.0006
0.02
0.04
1.0E-04
0.0004
0.1
0.01
0.02
5.0E-05
0.0002
0
0.0E+00
0
0
0
80
90
100
110
120
130
140
150
160
80
100
120
140
160
80
90
100
110
120
130
140
150
160
a) number of documents
b) number of documents
c) number of documents
Fig. 4. Forgetting the third topic of interest: a) f. 1b) f. 2c) f. 3d) f. 4d) f. 5f) f. 6
This facilitates the comparison between C and V, but obscures fluctuations in
the individual scores of the persistent topics.
The results indicate that through self-organisation Nootropia can adapt suc-
cessfully to a variety of changes in the user interests. Figure 2 indicates that two
topics of interest can be learned in parallel. In most cases, despite fluctuations
the final AUP of the involved topics is larger than zero. We can also observe
that the fluctuations in score between topics in the same task are usually sym-
metric. Although they are exaggerated due to the fixed number of evaluation
documents 7 , they are nevertheless indicative of the profile's ability to quickly
adapt to short-term variations in the user's interests.
7 Documents relevant to each topic compete for a place in the list of 3000 evaluation
documents.
 
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