An artificial neural network that recognizes an ordered set of words in text mining

This paper presents an artificial neural network based tool that locates an ordered set of words in a text. The network model is essentially a single layer network similar to Hopfield model that uses a Hebbian approach to activate the feature layer nodes (see section 2). This model was initially developed to go with our Connectionist Associative Memory Model (CAMM) and later found to be useful in text mining tasks as well. Further additions of features are currently under way to generate statistics and structural graphs based on semantic relationships.