I need some normative data on the semantic relation between categories. Particularly, I need coordinate values for these categories in a semantic space. The best I can find on this topic so far is Cree & McCrae (2003). They offer distance calculations between categories. However, I need the coordinate locations of each of the categories in the space they are projected onto.
For instance, the semantic difference between the categories herbivore and insect might be represented as a cosine of 5. However, I would need to know that the location of insect in the space it is projected is 3 and for herbivore it is 12.
Thanks!
Brandon
http://psycnet.apa.org/psycinfo/2003-03979-003
Peter Gärdenfors has done research on that topic.
Search for 'geometry of thought' and 'conceptual spaces'.
I'm using a semantic net for associative search
in my databases. Using the shortest path for
semantic distance is not the best idea since
a shortest path may lead through a vertex which
happens to have hundreds of connections.
Instead I use random walks and use the logarithm
of visit rank as a measure for semantic distance.
http://www.augos.com/ki/semnet_en.html
Networks come along with their own space.
Coordinates of a vertex v in the net could be defined
as vector of distances to some fixed chosen base
vertices v0, v1, v2...
It is also possible to embed the network topology
into Euklidean space, 2D (Cortex) or 3D. This could
be done with Kohonen learning, autoencoder, or
an evolutionary algorithm. It should be mentioned
that the brain has a grid architecture where each
neuron has its address as 3D coordinates. This has
been found by means of diffuctions tensor imaging.
But in reality a symbol's representation might
be distributed or encoded in waves.
Literature:
http://www.nature.com/nsu/020701/020701-2.html
http://www.technologyreview.com/view/541356/king-man-woman-queen-the-marvelous-mathematics-of-computational-linguistics/
http://www.eurekalert.org/pub_releases/2009-08/sicp-wts081109.php
http://arxiv.org/abs/1211.4709
http://www.cs.technion.ac.il/~shaulm/papers/pdf/Gabrilovich-Markovitch-ijcai2007.pdf
http://arxiv.org/abs/1009.0670
http://pespmc1.vub.ac.be/CLUSTERW.html
http://www.cs.bris.ac.uk/~steve/networks/congopaper/graphs/word_association_graph_USF-edges.txt
http://wis-wander.weizmann.ac.il/basic-principles-of-communication
http://www.kuleuven.be/semlab/interface/index.php
Regards,
Joachim
I'm not sure whether I understood the question properly but probably these works may be useful for you:
D.Rubin. 51 properties of 125 words: a unit analysis of verbal behavior
D. Lynott, L. Conell. Modality exclusivity norms for 423 object properties
B. Juhasz, M. Yap. Sensory experience ratings for over 5,000 mono- and disyllabic
words
O. Marchenko. Psycholinguistic database for semantic categories (this one is only in Russian as far as I know)
Bennett S. D. R., Burnett A. N., Siakaluk P. D., Pexman P. M. Imageability and body-object interaction ratings for 599 multisyllabic nouns.
Brysbaert M., Warriner A.B., Kuperman, V. (2014). Concreteness ratings for 40 thousand generally known English word lemmas.
Clark J. M., Paivio A. Extensions of the Paivio, Yuille, and Madigan (1968) norms.
Juhasz B. J., Lai Y.-H., Woodcock M.L. A database of 629 English compound words: ratings of familiarity, lexeme meaning dominance, semantic transparency, age of acquisition, imageability, and sensory experience.
Lynott D., Connell L. (2013). Modality exclusivity norms for 400 nouns: The relationship between perceptual experience and surface word form.
Moreno-Martínez F. J., Montoro P. R., Rodríguez-Rojo I. C. Spanish norms for age of acquisition, concept familiarity, lexical frequency, manipulability, typicality, and other variables for 820 words from 14 living/nonliving concepts.
Paivio A., Yuille J.C., Madigan S.A. (1968). Concreteness, imagery, and meaningfulness values for 925 nouns.
Schröder A., Gemballa T., Ruppin S., Wartenburger I. German norms for semantic typicality, age of acquisition, and concept familiarity.
Tillotson S.M., Siakaluk P.D., Pexman P.M. Body–object interaction ratings for 1 618 monosyllabic nouns.
These databases can be used to estimate the difference (or distance) between words or their groups, although many of them are developed in the framework of embodiment, and your question is about networking models if I'm not mistaken.
Also associative norms can be used for this purpose, they can be found in associative dictionaries, e.g. for Russian this one is avaliable online: http://tesaurus.ru/dict/dict.php
If you have a complete pairwise table or list of of cosines (correlation coefficients), you can use them for multidimensional scaling (after converting them to distances, which is easy in R). That will give you their coordinates in a multimensional space.
Well, I think your question is definitely culture oriented. To make a long story short, I can tell you to stick on the cultural differences. Analyze them, categorize them. Then you can find some solutions for categorizing similarity norms. Sociolinguistics and of course the role of culture in the norms of a society can be instrumental, by the way
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