Analogies between language and the immune system

Striking analogies between human language and the immune system was first suggested by Jerne, an immunologist, in his Nobel lecture. Inspired by Jerne´s opinion, we re-exploit these analogies between them, and propose that words can be regarded as B cells. Based on this proposed analogous comparison, a multi-word-agent autonomous learning model (MWAALM) is designed and implemented to learn the strengths of combinative relations between words, which are the rules dominating the order by that words compose a sentence. The model is validated on the task of dependency parsing and the task of word similarity computing. Results show that MWAALM obtains good performance on the two tasks, and analogies between words and B cells are proven to be plausible.