Abstract: An internet information agent accepts a reference document, performs an analysis upon it in accordance with metrics defined by its analysis algorithm and obtains respective lists (word, character-level n-gram, word-level n-gram), derives weights corresponding to the metrics, applies the metrics to a candidate document and obtains respective returned values, applies the weights to the returned values and sums the results to obtain a Document Dissimilarity (DD) value. This DD is compared with a Dissimilarity Threshold (DT) and the candidate document is stored if the DD is less than the DT. A user can apply relevance values to the search results and the agent modifies the weights accordingly. The agent can be used to improve a language model for use in speech recognition applications and the like.

Abstract: A neutral net in which new nodes and connections are created in both input and intermediate layers during training, which is by punishment, reward and teaching. This can use a small increase in memory requirement to preclude the necessity for long training times applicable problems in speech and natural language processing, video recognition and simple logic functions.