Diapositive 1

Overwiew & Objectives

	lexical semantic representations
		conceptual vector model (cvm)
		autonomous learning by the system
		from a given Ç semantic space È (ontology)
	Constructing texonomies
		Hierarchical - findind hyperonyms
		Multiple inheritance - views
		ambiguity as noise
	towards self contained WSD annotations
		Ç I made a deposit at the bank È
		Þ Ç I made a deposit at the bank<g:money> È

Conceptual vectors vector space

	An idea
		Concept combination Ñ a vector
	Idea space
		= vector space
	A concept
		= an idea = a vector V
		with augmentation: V + neighboorhood
	Meaning space
		= vector space + {v}*

2D view of Ç meaning space È

Conceptual vectors Thesaurus

	H : thesaurus hierarchy Ñ K concepts
		Thesaurus Larousse = 873 concepts
	V(Ci) : <a1, É, ai, É , a873>
		aj = 1/ (2 ** Dum(H, i, j))

Conceptual vectors Concept c4:peace

Conceptual vectors Term ÒpeaceÓ

Diapositive 8

Angular distance

	DA(x, y)  = angle (x, y)
		0 £ DA(x, y) £ p
		if 0 then x & y colinear Ñ same idea
		if p/2 then nothing in common
		if p then DA(x, -x) with -x  Ñ anti-idea of x

Angular distance

	DA(x, y) = acos(sim(x,y))
	DA(x, y) = acos(x.y/|x||y|))
			DA(x, x) = 0
			DA(x, y) = DA(y, x)
			DA(x, y) + DA(y, z) ³ DA(x, z)
			DA(0, 0) = 0  and  DA(x, 0) = p/2 by definition
			DA(ax, by) = DA(x, y) with ab > 0
			DA(ax, by) = p - DA(x, y) with ab < 0
			DA(x+x, x+y)  = DA(x, x+y) £ DA(x, y)

Thematic distance

	Examples
		DA(tit, tit) = 0
		DA(tit, passerine) = 0.4
		DA(tit, bird) = 0.7
		DA(tit, train) = 1.14
		DA(tit, insect) = 0.62

Some vector operations

2D view of weak contextualization

Autonomous learning 1/2

Autonomous learning 2/2

Diapositive 16

Hyperonyms identifications

Diapositive 18

Diapositive 19

Diapositive 20

Last words

	Switching of representation
		From subsymbolic to symbolic
		É and vice-versa Þ readabily of symbols É of words
	global and local test functions
		for vector quality assessment
		decision taking about number of meanings É or views
		detectors when combined to lexical functions (antonymy, etc.)
	the basis for
		self adjustement toward a vector space of constant density
		wsd as a reduction of noise (in context or out of context)
		unification of ontologies
		self emergent structuration of terminology