Information Filtering via Biased Random Walk on Coupled Social Network

<div class="floats-full-page floats-full-page-other"><h2>Table 2</h2><div class="floats-full-page-caption">Algorithmic performance for <i>Epinions</i> data set with recommendation list <svg height="11.375" id="M183" style="vertical-align:-0.17555pt" version="1.1" viewbox="0 0 45.575001 11.375" width="45.575001" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
<g transform="matrix(.017,-0,0,-.017,.062,11.112)"><path d="M559 163q-23 -66 -68 -163h-474l6 26q62 4 79.5 19.5t28.5 75.5l78 409q7 35 8.5 49t-8 25t-24 13t-51.5 5l5 28h266l-6 -28q-65 -5 -79.5 -18t-25.5 -74l-76 -406q-10 -57 14 -75q12 -13 96 -13q93 0 126 29q41 40 76 109z" id="x1D43F"></path></g><g transform="matrix(.017,-0,0,-.017,14.477,11.112)"><path d="M535 323h-483v50h483v-50zM535 138h-483v50h483v-50z" id="x3D"></path></g><g transform="matrix(.017,-0,0,-.017,29.181,11.112)"><path d="M412 140l28 -9q0 -2 -35 -131h-373v23q112 112 161 170q59 70 92 127t33 115q0 63 -31 98t-86 35q-75 0 -137 -93l-22 20l57 81q55 59 135 59q69 0 118.5 -46.5t49.5 -122.5q0 -62 -29.5 -114t-102.5 -130l-141 -149h186q42 0 58.5 10.5t38.5 56.5z" id="x32"></path></g><g transform="matrix(.017,-0,0,-.017,37.341,11.112)"><path d="M241 635q53 0 94 -28.5t63.5 -76t33.5 -102.5t11 -116q0 -58 -11 -112.5t-34 -103.5t-63.5 -78.5t-94.5 -29.5t-95 28t-64.5 75t-34.5 102.5t-11 118.5q0 58 11.5 112.5t34.5 103t64.5 78t95.5 29.5zM238 602q-32 0 -55.5 -25t-35.5 -68t-17.5 -91t-5.5 -105&#10;q0 -76 10 -138.5t37 -107.5t69 -45q32 0 55.5 25t35.5 68.5t17.5 91.5t5.5 105t-5.5 105.5t-18 92t-36 68t-56.5 24.5z" id="x30"></path></g>
</svg>.</div><div class="floats-full-page-content"><table class="table-group" id="tab2"><tr><td><table class="table"><tr><td class="thead-hr" colspan="6"><hr /></td></tr><tr class="thead"><td align="left">Method </td><td align="center"><span style="width: 7.3000002px;"><svg height="7.9499998" id="M184" style="vertical-align:-0.0pt" version="1.1" viewbox="0 0 7.3000002 7.9499998" width="7.3000002" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
<g transform="matrix(.017,-0,0,-.017,.062,7.675)"><path d="M393 379q-9 -16 -28 -29q-15 -10 -23 -2q-19 19 -36 19q-21 0 -52 -38q-57 -72 -82 -126l-40 -197q-23 -3 -75 -18l-7 7q49 196 74 335q7 43 -2 43q-7 0 -30 -14.5t-47 -37.5l-16 23q37 42 82 73t67 31q41 0 15 -113l-11 -50h4q41 71 85 117t77 46q29 0 45 -26&#10;q13 -21 0 -43z" id="x1D45F"></path></g>
</svg></span></td><td align="center">Precision </td><td align="center">Recall </td><td align="center"><svg height="11.175" id="M185" style="vertical-align:-0.0pt" version="1.1" viewbox="0 0 10.7 11.175" width="10.7" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
<g transform="matrix(.017,-0,0,-.017,.062,11.113)"><path d="M599 650l-18 -160l-30 -2q-2 70 -11 94q-5 16 -26 24t-75 8h-94q-27 0 -33.5 -6.5t-12.5 -32.5l-43 -226h108q52 0 72.5 5t31 18t28.5 52h28l-40 -200h-28q-1 42 -6 56.5t-24.5 21t-70.5 6.5h-108l-32 -177q-13 -65 1 -80.5t88 -22.5l-8 -28h-279l6 28q61 5 77.5 20.5&#10;t29.5 81.5l72 387l7.5 40.5t1 26.5t-4 18t-15.5 10t-24 6t-37 4l8 28h461z" id="x1D439"></path></g>
</svg>-measure</td><td align="center">HD</td></tr><tr><td class="thead-hr" colspan="6"><hr /></td></tr><tr><td align="left">MD </td><td align="center">0.172 </td><td align="center">0.036 </td><td align="center">0.099 </td><td align="center">0.046 </td><td align="center"><b>0.673</b></td></tr><tr><td align="left">UCF </td><td align="center">0.186 </td><td align="center">0.033 </td><td align="center">0.090 </td><td align="center">0.041 </td><td align="center">0.56</td></tr><tr><td align="left">RW </td><td align="center"><b>0.171</b></td><td align="center"><b>0.036</b></td><td align="center"><b>0.1</b></td><td align="center"><b>0.046</b></td><td align="center">0.652</td></tr><tr class="table-tr"><td colspan="6"><hr class="tbody-hr" /></td></tr></table></td></tr></table></div></div>

Table 2 | Information Filtering via Biased Random Walk on Coupled Social Network

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Table 2: Information Filtering via Biased Random Walk on Coupled Social Network

description

Table 2

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