Design of Automatic Extraction Algorithm of Knowledge Points for MOOCs

<table class="table-group" id="tab2"><tr><td><table class="table"><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr class="thead"><td align="left">Parameters</td><td align="center">The 1st level of knowledge points</td><td align="center">The 2nd level of knowledge points</td></tr><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr><td align="left">The expert annotation number of knowledge points</td><td align="center">66</td><td align="center">258</td></tr><tr><td align="left">Extract expert annotation number of knowledge points</td><td align="center">48</td><td align="center">193</td></tr><tr><td align="left">Accuracy rate</td><td align="center">72.7%</td><td align="center">74.8%</td></tr><tr class="table-tr"><td colspan="3"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

The results of accuracy rate of two level knowledge points.

Computational Intelligence and Neuroscience

tab2

Table 2

Table 2: Design of Automatic Extraction Algorithm of Knowledge Points for MOOCs 