ECTOR is intended to be a intelligent chatterbot, so it has to make nodes from sentences (in the sense of BAsCET). Each sentence is cut into each of its words, and each word is linked to its neighbour(s), but also to the node representing the sentence itself (see integration of words in a Concept Network).
Words often have several semantics, that's why a concept is a combination of several words (see a word is not a concept). Actually, an expression gives a particular sense to all the words it contains.
Moreover, some words are often related, and have a particular sense when associated (like "neural" and "network"). That's why we can create a new semantic node in the concept Network when a sequence of words co-occurs equally.
+---(2)---> many(4)
|
v
there (5) <----(4)---> has (10) <----(4)---> been (6)
^
| |
| +---(1)--> several(1)
|
| CREATION OF "there as been"
v
there has been(4)
^ ^ ^
| | |
+--(4)---+ (4) +--(4)---+ +--(2)--> many(4)
| | | |
v | v v
there(5) <--(4)--> has(10) <--(4)--> been(6)
^
|
+--(1)--> several(1)
When a phrase is added, the higher level concepts (higher than words) are also considered. Example: addition of the phrase there has been something.
there has been(5)
^ ^ ^
| | |
+--(5)---+ (5) +--(5)---+ +--(2)--> many(4)
| | | |
v | v v
there(6) <--(5)--> has(11) <--(5)--> been(7) <--(1)--> something(1)
^
|
+--(1)--> several(1)
In order to create a concept, all the nodes to be integrated must have an equivalent (95%) co-occurrence.
The created node then has a number of occurrences equal to the minimum of the co-occurrences considered.
"Creating" nodes influence the new one, but this one influences only the first and last constituents of the string.
A created node can be a sub-concept of another existing one (for example a sentence, or another created concept).
s e n t e n c e
| | | |
+-+ | | +--+
| | | |
word1--word2--word3--word4
NEW CONCEPT WITH WORDS 1 TO 3
s e n t e n c e
| |
created +--- word4 -+
node |
| | | |
word1 ---+ | +---- word3 ------+
|
word2