Title :
Seeking signals in data bases using neural networks
Author :
Stebbins, George
Author_Institution :
Adv. Policy Inst., California Univ., Los Angeles, CA, USA
Abstract :
This paper presents a strategy to allow searching a database using information that is not originally in the database. A backpropagation neural network is proposed that learns correlations between data items in the database and generates predictions. This network technique is applied to the problem of predicting housing code violations, given census data, and other problem property data. A problem is discovered in determining the categorization of the data, and a possible solution is proposed
Keywords :
backpropagation; correlation methods; data mining; neural nets; public administration; signal processing; backpropagation neural network; census data; damaged data; data categorization; data item correlation learning; data mining; database searching; housing code violations; knowledge discovery; missing data; predictions; property data; signal seeking; Artificial neural networks; Backpropagation; Cities and towns; Convergence; Databases; Information retrieval; Inspection; Intelligent networks; Neural networks; Self organizing feature maps;
Conference_Titel :
Signal Processing and Its Applications, 1999. ISSPA '99. Proceedings of the Fifth International Symposium on
Conference_Location :
Brisbane, Qld.
Print_ISBN :
1-86435-451-8
DOI :
10.1109/ISSPA.1999.818139
