DocumentCode :
279082
Title :
The textural language machine: a system of associative electronic networks for efficient processing of neural language texts
Author :
Hilberg, W.
Author_Institution :
Tech. Univ. of Darmstadt
Volume :
i
fYear :
1991
fDate :
8-11 Jan 1991
Firstpage :
219
Abstract :
A novel digital electronic system is presented, which is able to handle the human language very well. In contrast to conventional computers this can be obtained by the following measures: by concatenation of well-known associative memories with feedback, by the introduction of conditional association operations, and by a strategy for the stepwise abstraction of texts (in the opposite direction by a process of concretization). The resulting structure is a system of networks which matches very well with the process network of human language, which could be found by analyzing large amounts of texts. The efficiency of the language machine can be increased by using an appropriate learning strategy. Experimental results showed that it is possible to master large stocks of words right from the beginning. It can be seen that the process of abstraction yields high data compression values hitherto unthought of. Possible applications are the storage of large amounts of texts, the transmission of texts over great distances, the translation of texts into another language and the encoding and ciphering of texts
Keywords :
natural languages; neural nets; abstraction; associative electronic networks; associative memories; conditional association operations; data compression; learning strategy; neural language texts; textural language machine; Associative memory; Data compression; Encoding; Feedback; Humans; Machine learning; Natural languages; Neural networks; Neurons; Supercomputers;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
System Sciences, 1991. Proceedings of the Twenty-Fourth Annual Hawaii International Conference on
Conference_Location :
Kauai, HI
Type :
conf
DOI :
10.1109/HICSS.1991.183889
Filename :
183889
Link To Document :
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