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Example of a semantic network

A semantic network is a network which represents semantic relations among concepts. This is often used as a form of knowledge representation. It is a directed or undirected graph consisting of vertices, which represent concepts, and edges.[1]

Contents

History

"Semantic Nets" were first invented for computers by Richard H. Richens of the Cambridge Language Research Unit in 1956 as an "interlingua" for machine translation of natural languages.

They were developed by Robert F. Simmons at System Development Corporation in the early 1960s and later featured prominently in the work of Allan M. Collins and colleagues (e.g., Collins and Quillian;[2][3] Collins and Loftus).[4]

In the 1960s to 1980s the idea of a semantic link was developed within hypertext systems as the most basic unit, or edge, in a semantic network. These ideas were extremely influential, and there have been many attempts to add typed link semantics to HTML and XML.

Semantic network construction

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WordNet

An example of a semantic network is WordNet, a lexical database of English. It groups English words into sets of synonyms called synsets, provides short, general definitions, and records the various semantic relations between these synonym sets. Some of the most common semantic relations defined are meronymy (A is part of B, i.e. B has A as a part of itself), holonymy (B is part of A, i.e. A has B as a part of itself), hyponymy (or troponymy) (A is subordinate of B; A is kind of B), hypernymy (A is superordinate of B), synonymy (A denotes the same as B) and antonymy (A denotes the opposite of B).

WordNet properties have been studied from a network theory perspective and compared to other semantic networks created from Roget's Thesaurus and word association tasks. From this perspective the three of them are a small world structure.[5]

It is also possible to represent logical descriptions using semantic networks such as the existential Graphs of Charles Sanders Peirce or the related Conceptual Graphs of John F. Sowa.[1] These have expressive power equal to or exceeding standard first-order predicate logic. Unlike WordNet or other lexical or browsing networks, semantic networks using these representations can be used for reliable automated logical deduction. Some automated reasoners exploit the graph-theoretic features of the networks during processing.

Other examples

Other examples of semantic networks are Gellish models. Gellish English with its Gellish English dictionary, is a formal language that is defined as a network of relations between concepts and names of concepts. Gellish English is a formal subset of natural English, just as Gellish Dutch is a formal subset of Dutch, whereas multiple languages share the same concepts. Other Gellish networks consist of knowledge models and information models that are expressed in the Gellish language. A Gellish network is a network of (binary) relations between things. Each relation in the network is an expression of a fact that is classified by a relation type. Each relation type itself is a concept that is defined in the Gellish language dictionary. Each related thing is either a concept or an individual thing that is classified by a concept. The definitions of concepts are created in the form of definition models (definition networks) that together form a Gellish Dictionary. A Gellish network can be documented in a Gellish database and is computer interpretable.

Software tools

There are also elaborate types of semantic networks connected with corresponding sets of software tools used for lexical knowledge engineering, like the Semantic Network Processing System (SNePS) of Stuart C. Shapiro[6] or the MultiNet paradigm of Hermann Helbig,[7] especially suited for the semantic representation of natural language expressions and used in several NLP applications.

See also

Examples

References

  1. ^ a b John F. Sowa (1987). "Semantic Networks". in Stuart C Shapiro. Encyclopedia of Artificial Intelligence. http://www.jfsowa.com/pubs/semnet.htm. Retrieved 2008-04-29. 
  2. ^ Allan M. Collins; M.R. Quillian (1969). "Retrieval time from semantic memory". Journal of verbal learning and verbal behavior 8 (2): 240–248. doi:10.1016/S0022-5371(69)80069-1. 
  3. ^ Allan M. Collins; M. Ross Quillian (1970). "Does category size affect categorization time?". Journal of verbal learning and verbal behavior 9 (4): 432–438. doi:10.1016/S0022-5371(70)80084-6. 
  4. ^ Allan M. Collins; Elizabeth F. Loftus (1975). "A spreading-activation theory of semantic processing". Psychological Review 82 (6): 407–428. doi:10.1037/0033-295X.82.6.407. 
  5. ^ Steyvers, M.; Tenenbaum, J.B. (2005). "The Large-Scale Structure of Semantic Networks: Statistical Analyses and a Model of Semantic Growth". Cognitive Science 29 (1): 41–78. doi:10.1207/s15516709cog2901_3. 
  6. ^ Stuart C. Shapiro
  7. ^ Hermann Helbig

Further reading

  • Allen, J. and A. Frisch (1982). "What's in a Semantic Network". In: Proceedings of the 20th. annual meeting of ACL, Toronto, pp. 19-27.
  • John F. Sowa, Alexander Borgida (1991). Principles of Semantic Networks: Explorations in the Representation of Knowledge.

External links


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