Neural network for electronic search applications

Details Neural network for electronic search applications Neural network for electronic search applications

2011-07-12

2011-07-12

Gaffin, Jeffrey A (Department: 2129)

Data processing: artificial intelligence

Neural network

Learning task

C706S018000, C706S031000

Reexamination Certificate

active

07979370

ABSTRACT:
A system for information searching includes a first layer and a second layer. The first layer includes a first plurality of neurons each associated with a word and with a first set of dynamic connections to at least some of the first plurality of neurons. The second layer include a second plurality of neurons each associated with a document and with a second set of dynamic connections to at least some of the first plurality of neurons. The first set of dynamic connections and the second set of dynamic connections can be configured such that a query of at least one neuron of the first plurality of neurons excites at least one neuron of the second plurality of neurons. The excited at least one neuron of the second plurality of neurons can be contextually related to the queried at least one neuron of the first plurality of neurons.

REFERENCES:
Hämäläinen et al., TUTNC: a general purpose parallel computer for neural network computations, 1995.
Shmelev et al., Equilibrium Points of Single-Layered Neural Networks with Feedback and Applications in the Analysis of Text Documents, 2005.
Bengio et al., “A Neural Probabilistic Language Model,” Journal of Machine Learning Research (3) 2003 pp. 1137-1155.
K.L. Kwok, “A Neural Network for Probabilistic Information Retrieval,” Western Connecticut State University, 1989, pp. 21-30.
Qin He, “Neural Network and Its Application in IR,” Graduate School of Library and Information Science, University of Illinois at Urbana-Champaign Spring, 1999, 31 pages.

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