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SymText and its successor, MPLUS, make extensive use of semantic networks for semantic analysis.
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The new model of semantic networks using the adaptive associative memories can do inference extremely fast — in time that does not increase with the size of knowledge base.
We use a combination of semantic network analysis and network centrality measures to overcome these particular challenges and to explore the dynamic structural space of concepts in formalized documents pertaining to the recent financial crisis.
Steyvers, M. & Tenenbaum, J. B. The large-scale structure of semantic networks: Statistical analyses and a model of semantic growth.
The large-scale structure of semantic networks: statistical analyses and a model of semantic growth.
Bra79 Ronald J. Brachman, On the Epistomological Status of Semantic Networks.
Dopaminergic modulation of semantic network activation.
For a review of network analysis generally and these statistics in particular see [1][30], and for use in semantic networks see [5][9][14].
The methods discussed above are thus only of limited use for assessing semantic networks.
Use of universal probabilistic semantic networks like Probase to enrich the text adds far more context and meaning, enabling for better classification.
We present the implementation of inflectional morphology of Bulgarian possessive and reflexive-possessive pronouns using the semantic networks interpretation.
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CEO of Professional Science Editing for Scientists @ prosciediting.com