1. A method implemented by a stylus-based personal computer for recognizing handwriting of a particular user, the method comprising: storing a set of handwriting samples of a particular user; receiving a handwritten inputs from the particular user for recognition; separately providing the handwritten input to first and second recognition engines, respectively, each of the first and second recognition engines applying a separate process for recognizing the handwritten input; producing by the recognition process of the first recognition engine a first list of alternative classifications of the handwritten input by matching features of the handwritten input to features of the stored handwriting samples of the particular user, each of the classifications of the first list comprising a potential character with an associated recognition probability; producing by the recognition process of the second recognition engine a second list of alternative classifications of the handwritten input without utilizing the stored handwriting samples, the process of the second recognition engine being designed to generically recognize handwriting for a plurality of users, each of the classifications of the second list comprising a potential character with an associated recognition probability; applying data of the handwritten input, the first list, and the second list to a comparative neural network for processing, the applied data including a context feature of the handwritten input, a descriptive feature of a potential character and an associated recognition probability from the first list, and a descriptive feature of a potential character and an associated probability from the second list; outputting a character as a recognition result of the handwritten input based on the processing of the neural network, the outputted character being one of the potential characters in the first and second lists; and adapting the stored set of handwriting samples by adding a previously received handwritten input from the particular user to the set before a subsequently received handwritten input from the particular user is provided to the first and second recognition engines, wherein the neural network is configured to merge the first and second lists by coalescing common classifications of the handwritten input in the first and second lists, wherein the neural network is based on a computational model comprising a group of interconnected processing units, and wherein the recognition process of the first recognition engine matches context features of the subsequently received handwritten input to the context features of the adapted set of handwriting samples to produce the first list for the subsequently received handwritten input.