To solve the problem of Deep Web data sources topic classification, this paper proposed a quantum self-organization feature mapping network model(DR-QSOFM)with a classification algorithm. DR-QSOFM combines quantum computation and traditional SOFM, and relies the feature vectors and target vectors incoordinately in different phases of training, making a more centralized distribution of winner neurons in competitive layer and more obvious boundaries among clusters. Some experiments are designed and done on the expanded TEL-8 dataset to test the validity of DR-QSOFM.
A Framework for Extracting Information from Semi-Structured Web Data Sources