![]() ![]() ![]() Weak semantic maps are unique in two key aspects: (i) the semantic characteristics captured by weak semantic mapping apply to all domains of knowledge, i.e., they are “universal” (ii) the geometry of the map only captures the universal aspects of semantics, while remaining independent of other, domain-specific semantic aspects. In this case, the principal spatial components of the distribution (defining the axes of the map) have consistent semantics that can be approximately characterized as valence, arousal, freedom, and richness, thus providing metrics related to affective spaces and feature maps (e.g., ). We have recently introduced the alternative approach of weak semantic mapping, in which words or concepts are allocated in space based on semantic relationships such as synonymy and antonymy. Their complete characterization, as well as the extension of results to non-linguistic materials, remains an open challenge. Residual analysis of available linguistic resources, such as WordNet, suggests that the number of universal semantic dimensions representable in natural language may be finite. The practical utility of the new and prior dimensions is illustrated by the automated evaluation of different kinds of documents. senses implies a non-trivial trade-off between rich and unambiguous information due to homonymy and polysemy. Interestingly, the choice of using relations among words vs. ![]() We show that the “completeness” dimension derived from the holonym/meronym relation is independent of, and practically orthogonal to, the “abstractness” dimension derived from the hypernym-hyponym (“is-a”) relation, while both dimensions are orthogonal to the maps derived from synonymy and antonymy. Specifically, we employ semantic relationships not previously used for weak semantic mapping, such as holonymy/meronymy (“is-part/member-of”), and we compare maps constructed from word senses to those constructed from words. Here we address questions of the number, quality, and mutual independence of the weak semantic dimensions. We previously introduced the notion of weak semantic map: a metric space allocating concepts along their most general (universal) semantic characteristics while at the same time ignoring other, domain-specific aspects of their meanings. A key to semantic analysis is a precise and practically useful definition of meaning that is general for all domains of knowledge. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |