Recommendation of Potential Friends from E-Mail Networks
| Autor: | Ching-Ya Chen, 陳青雅 |
|---|---|
| Rok vydání: | 2016 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 104 The recipient recommendation has been the feature of email clients and webmail services in recent years. However, the recommended list of these features often only contains frequent contacts. There are no contacts who referred to correlation between the email contents and the discussion group included. These results in recommended recipients include some contacts who should not belong to the related discussion group, and thus it affects the accuracy of the recommendation. In this viewpoint, this paper provides an approach for recipient recommendation which depends on the correlation between the email contents and the discussion group. The approach contains three modules. The preprocessing module retrieves contents and subjects from Enron email dataset central first, and then fetches nouns through some processes such as deleting email header, part-of-speech tagging and removing Stopwords. The recommendation module calculates the entropy of the nouns in each to pick up keywords, and then clusters emails which are similar with new email into a discussion group by cosine similarity measurement. Moreover this research also analyzes the keywords and contacts in discussion group to generate the list of recommended recipients. Finally, this proposed approach is verified by a real email. Obviously, the result show the proposed recommendation approach by the contents and contacts in similar emails is pretty workable. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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