Labeled links are Concept Network links with label.

Labels are nodes whose activation value modifies the influence of a node on another one.

                  +------------+
                  | opposite (3|
                  +------------+
+---------+              |               +-----------+
| happy (1|<-------------+-------------->| unhappy (2|
+---------+                              +-----------+

Let C₁ be the occurrence number of the word 1 -happy- Let C_1,2 be the co-occurrences number of the words 1 and 2.
Let A₃ be the activation level of word 3 -opposite, the label node-
Let I_1,2 the percentage of influence of the node 1 on the node 2.

I_1,2 = C_1,2 / C₁ + (1 - C_1,2 / C₁) x A₃

In this example, there is a link between happy and unhappy, that are closely related (in real world), but not conceptually similar.

This facts could be translated in:

not conceptually similar

Their number of co-occurrences is low, related to their number of occurrences (C_1,2 1 and C_1,2 2)

closely related

when you look for the opposite of happy, you should find unhappy: when the node happy is activated (A_happy = 100) and the node opposite is activated (A₃ = 100), then, after activation propagation, using the formula for influence given upper, the node unhappy will be activated.

For example: say that happy occurred 16 times in the corpus used to build the Concept Network, that unhappy occurred 3 times in the same corpus, and that they appeared 2 times in the same sentences, here are the value to give to the variables:

• C₁ = 16
• C₂ = 3
• C_1,2 = 2

I_1,2 = 2 / 16 + (1 - 2 / 16) x 100% = 100%

On the contrary, when AV_opposite = 0%, I_1,2 = 2 / 16 + (1 - 2 / 16) x 0% = 12.5%, so that when happy is activated, unhappy is not much activated through activation propagation.