 <p>I think you are going the wrong way. Backpropagation isn't a good choice for this type of learning (somehow incremental learning). To use backpropagation you need some data, say 1000 data where <strong>different types of similaritiy (input)</strong> and the <strong>True Similarity (output)</strong> are given. Then weights will update and update until error rate comes down. And besides you need test data set too that will make you sure the result network will do good even for similarity values it didn't see during training.</p>