E-mail based communication is gradually making its way into the distant collaborative learning environment. However, compared with the traditional lecture cum discussion learning environment, in e-mail-based collaborative discussion, it is difficult to know the latest status of the learners for providing immediate feedback effectively due to limited information resources. We propose an information retrieval method for mailing list review. Relevant nouns, as the keywords in a message, were pulled out from e-mails, and summary was extracted by these keywords. Japanese natural language processing technology is employed in the proposed method. These extraction procedures are used to form the basis for the Web-based mailing list reference application with the additional function of substituting Hiragana characters for the Chinese characters in a message. We claim that these features in the proposed method help to identify an outline of discussion topics in a mailing list, and improve the readability of e-mails. Furthermore, we have conducted statistical evaluation of this method as an effectiveness study. We compared between the extraction result of 46 undergraduate students and the algorithm result of extraction method. The result suggests that the proposed method can detect major sentences in e-mail articles properly.
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