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This spreadsheet shows the results of training a series of Support Vector Machine (SVM) classifiers to replicate the decision process for identifying e-mails of business value from among 846 e-mails in two corporate mailboxes. One set of SVMs were trained on emails without including the text of attachments and with the inclusion of attachments. For the sake of comparison, these SVMs were also trained on Spam / Ham and on a randomly selected subset of Enron emails half of which were arbitrarily tagged as "business value".
E-mail, Machine learning, Record, Business value, Automatic classification
E-mail, Machine learning, Record, Business value, Automatic classification
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 19 | |
| downloads | 3 |

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