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Overwiew & Objectives

	Lexical soup
	what ? Bilingual dic & Conceptual vectors
	which heuristics ?
	for what ? linking decision and quality assessment

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}*

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

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
		tit = insectivorous passerine bird É

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Conclusion

	System in continuous learning
		Evolving results
		Hopefully converging
	Assisting and begin assisted by
		Vectorized lexical functions
		Human annotators
	Toward
		Community of lexical agents
		Lexical knowledge negotiation