One of the main references, and other interesting stuff can be found on Bob Coecke's site: http://www.comlab.ox.ac.uk/bob.coecke/ http://www.comlab.ox.ac.uk/bo

One of the main references, and other interesting stuff can be found on Bob Coecke's site: http://www.comlab.ox.ac.uk/bob.coecke/ http://www.comlab.ox.ac.uk/bob.coecke/ Personally, I think the NLP problem is, and will always be, a graph problem. To the extent that you can approximate and accelerate graph algorithms with vectors, then fine, but vectors are not the fundamental space. One interesting aspect of Coecke's work is the reuse of Hilbert spaces and mathematical formalism from quantum mechanics. In fact, the most fascinating papers on his site are the ones where he simplifies and visualizes QM intuition based on monoidal categories, very much in the spirit of Baez & Stay: http://math.ucr.edu/home/baez/rosetta.pdf http://math.ucr.edu/home/baez/rosetta.pdf Neither Clarke nor Coecke give enough prominence to the great work of Aerts & Gabora on QM-style attribute spaces and 'collapse' of knowledge vectors, e.g. http://arxiv.org/abs/quant-ph/0402207 http://arxiv.org/abs/quant-ph/0402207 http://arxiv.org/abs/quant-ph/0402205 http://arxiv.org/abs/quant-ph/0402205 Coecke clearly knew of their work, even though he's now at Oxford, he did his PhD at the Free University of Brussels with A&G. Mik