A Summary Sentence Extraction Method for Web-based Mailing List Review Application and Its Effectiveness Study

E-mail based communication is gradually making its way into the distant collaborative learning environment. But, compared with traditional lecture cum discussion learning environment in e-mail-based collaborative discussion, it is difficult to know the latest statuses of the learners for providing immediate feedback effectively due to limited information resources. The authors propose an information retrieval method for mailing list review. Relevant nouns, as 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. The authors 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. Statistical evaluation of this method has been proceeded and it has been found as an effective retrieval method for e-mail-based communication. Also, The comparative experiment between the extraction result of 46 undergraduate students and the algorithm result of extraction method suggests that the proposed method can detect major sentences in e-mail articles properly.