A Dynamical Model for Information Retrieval and Emergence of Scale-Free
Clusters in a Long Term Memory Network
I. Licata. (2008)cite arxiv:0801.0887
Comment: 8 pages, 11 figures, 2 tables. Submitted to Emergence: Complexity and
Organization.
Abstract
The classical forms of knowledge representation fail when a strong dynamical
interconnection between system and environment comes into play. We propose here
a model of information retrieval derived from the Kintsch-Ericsson scheme,
based upon a long term memory (LTM) associative net whose structure changes in
time according to the textual content of the analyzed documents. Both the
theoretical analysis carried out by using simple statistical tools and the
tests show the appearing of typical power-laws and the net configuration as a
scale-free graph. The information retrieval from LTM shows that the entire
system can be considered to be an information amplifier which leads to the
emergence of new cognitive structures. It has to be underlined that the
expanding of the semantic domain regards the user-network as a whole system.
%0 Generic
%1 Licata2008
%A Licata, Ignazio
%D 2008
%K dynamical emergence network retrieval
%T A Dynamical Model for Information Retrieval and Emergence of Scale-Free
Clusters in a Long Term Memory Network
%U http://arxiv.org/abs/0801.0887
%X The classical forms of knowledge representation fail when a strong dynamical
interconnection between system and environment comes into play. We propose here
a model of information retrieval derived from the Kintsch-Ericsson scheme,
based upon a long term memory (LTM) associative net whose structure changes in
time according to the textual content of the analyzed documents. Both the
theoretical analysis carried out by using simple statistical tools and the
tests show the appearing of typical power-laws and the net configuration as a
scale-free graph. The information retrieval from LTM shows that the entire
system can be considered to be an information amplifier which leads to the
emergence of new cognitive structures. It has to be underlined that the
expanding of the semantic domain regards the user-network as a whole system.
@misc{Licata2008,
abstract = { The classical forms of knowledge representation fail when a strong dynamical
interconnection between system and environment comes into play. We propose here
a model of information retrieval derived from the Kintsch-Ericsson scheme,
based upon a long term memory (LTM) associative net whose structure changes in
time according to the textual content of the analyzed documents. Both the
theoretical analysis carried out by using simple statistical tools and the
tests show the appearing of typical power-laws and the net configuration as a
scale-free graph. The information retrieval from LTM shows that the entire
system can be considered to be an information amplifier which leads to the
emergence of new cognitive structures. It has to be underlined that the
expanding of the semantic domain regards the user-network as a whole system.
},
added-at = {2009-07-21T09:39:48.000+0200},
author = {Licata, Ignazio},
biburl = {https://www.bibsonomy.org/bibtex/22f8c7da5b17994315175109e7519ae78/kasimiro},
interhash = {9fdccb8d82bfe145031c8ba589f3491b},
intrahash = {2f8c7da5b17994315175109e7519ae78},
keywords = {dynamical emergence network retrieval},
note = {cite arxiv:0801.0887
Comment: 8 pages, 11 figures, 2 tables. Submitted to Emergence: Complexity and
Organization},
timestamp = {2009-07-21T09:40:28.000+0200},
title = {A Dynamical Model for Information Retrieval and Emergence of Scale-Free
Clusters in a Long Term Memory Network},
url = {http://arxiv.org/abs/0801.0887},
year = 2008
}