An Automatic Multidocument Text Summarization Approach Based on Naïve Bayesian Classifier Using Timestamp Strategy

<table class="table-group" id="tab5"><tr><td><table class="table"><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr class="thead"><td class="align_left" rowspan="2"> </td><td class="align_center" colspan="2">Length of summary generated by system</td></tr><tr class="thead"><td class="align_center">Short</td><td class="align_center">Long</td></tr><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr><td class="align_left">Professor</td><td class="align_center">3</td><td class="align_center">2</td></tr><tr><td class="align_left">Lecturers</td><td class="align_center">6</td><td class="align_center">3</td></tr><tr><td class="align_left">Students</td><td class="align_center">5</td><td class="align_center">1</td></tr><tr class="table-tr"><td colspan="3"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Comparison of length of summary generated by human and system.

The Scientific World Journal

tab5

Table 5

Table 5: An Automatic Multidocument Text Summarization Approach Based on Naïve Bayesian Classifier Using Timestamp Strategy 