Extracting Product Features and Opinion Words Using Pattern Knowledge in Customer Reviews

<table class="table-group" id="tab3"><tr><td><table class="table"><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr class="thead"><td align="left"> </td><td align="center">Number of tagged product features</td><td align="center">Number of review sentences</td></tr><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr><td align="left">Apex</td><td align="center">110</td><td align="center">739</td></tr><tr><td align="left">Canon</td><td align="center">100</td><td align="center">597</td></tr><tr><td align="left">Creative</td><td align="center">180</td><td align="center">1716</td></tr><tr><td align="left">Nikon</td><td align="center">74</td><td align="center">346</td></tr><tr><td align="left">Nokia</td><td align="center">109</td><td align="center">546</td></tr><tr class="table-tr"><td colspan="3"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Summary of tagged product features for each customer review dataset.

The Scientific World Journal

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Table 3

Table 3: Extracting Product Features and Opinion Words Using Pattern Knowledge in Customer Reviews 