DocumentCode
2772619
Title
Natural language neural network and its application to question-answering system
Author
Sagara, Tsukasa ; Hagiwara, Masafumi
Author_Institution
Grad. Sch. of Sci. & Technol., Keio Univ., Yokohama, Japan
fYear
2012
fDate
10-15 June 2012
Firstpage
1
Lastpage
7
Abstract
This paper proposes a novel neural network to treat natural language. Most of the conventional neural networks can only process sentences consisted of a few words, and their applications are very simple such as metaphor understanding. The proposed network can process many complicated sentences and can be used as an associative memory and a question-answering system. The proposed network is composed of 3 layers and one network: Sentence Layer, Knowledge Layer, Deep Case Layer and Dictionary Network. The input sentences are divided into knowledge units and stored in the Knowledge Layer. The Deep Case Layer play an important role to process the knowledge units properly. The Dictionary Network also plays an important role as a knowledge based. We have carried out several experiments and they have shown that the proposed neural network has superior performances as an associative memory and a question-answering system. Especially as a question-answering system, the performance is very close to the elaborated system based on artificial intelligence.
Keywords
content-addressable storage; knowledge based systems; natural language processing; neural nets; question answering (information retrieval); artificial intelligence; associative memory; deep case layer; dictionary network; knowledge based system; knowledge layer; knowledge units; metaphor understanding; natural language neural network; question-answering system; sentence layer; Algorithm design and analysis; Dictionaries; Programmable logic arrays; Reliability;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks (IJCNN), The 2012 International Joint Conference on
Conference_Location
Brisbane, QLD
ISSN
2161-4393
Print_ISBN
978-1-4673-1488-6
Electronic_ISBN
2161-4393
Type
conf
DOI
10.1109/IJCNN.2012.6252553
Filename
6252553
Link To Document