Information Technology Reference
In-Depth Information
3.3.3 The separation of the thinker and the thought
Thinking is not a PowerPoint presentation in which the thinker watches the stream of his
thoughts. When a person is dreaming or hallucinating, the thinker and his thought-stream
are not separate. They are blended together. The thinker inhabits his thoughts.
Gelernter describes thinking as a spectrum of many methods that alternate depending
on the current attentional focus. When the focus is high, the method is analytic and
sharp. When the brain is not sharply focused, emotions are more involved and objects
become fuzzy. That description is analogous to the filtering restriction: define sharp
clustering first and leave fuzzy clustering approaches for the final steps. As Gelernter
writes, “No computer will be creative unless it can simulate all the nuances of human
emotion.”
4. Case study
This section presents a sample case to illustrate the MLW procedure. The database is a set of
ten Web pages with the topic “Orchids”. From more than 4200 original symbols and
morphemes in the original pages, 3292 words were extracted; 67 of them were automatically
selected for the example. This section shows the sequential MLW decomposition. Table 4
shows the filtering results for the first six E
ci
s.
4.1 Build E
ci
1
Because the algorithm has no initial information about the text, we start with a transition
state and set the d parameter to 20%. This parameter assesses the difference in the number
of elements between the most and least populated partitions.
4.2 Apply filters to E
ci
1
The K-means clustering, in the following KM, is used as the first filter with settings N= 5
clusters, seed 10. Diff=16%<d. Keep KM as the filter.
4.3 Apply filters to E
ci
2
Filter using KM with the same settings, and the current Diff=11%<d. Keep KM as the
filter.
4.4 Apply filters to E
ci
3
Filter using KM with the same settings, and the current Diff=10%<d. Keep KM as the filter
and exit the transition state.
4.5 Apply filters to E
ci
4
Filter using KM with d=10% for steady state. This process will indicate whether to change
the filter or build a new E
ce
. Clustering settings are the same, and the current Diff=20%>d.
Change to Farthest First (FF) as the filter.
