A Collaborative Recommend Algorithm Based on Bipartite Community

<table>Results of UCBCR. It successively reports the rank accuracy, hitting rate, popularity, and diversity base on different length of recommend lists and different community structures under each parameter values. Illustrations <svg height="7.9499998" id="M283" style="vertical-align:-0.11285pt" version="1.1" viewbox="0 0 9.2749996 7.9499998" width="9.2749996" 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="M515 96q-37 -44 -84.5 -76t-71.5 -32q-12 0 -18 7t-6 34t10 75l19 89h-2q-87 -113 -181 -176q-43 -29 -83 -29q-46 0 -46 63q0 31 9 67l52 222q7 36 -1 36q-10 0 -76 -50l-13 24q47 45 92 71.5t67 26.5q18 0 21 -16.5t-8 -65.5l-56 -242q-16 -67 13 -67q41 0 114 74
t114 146l32 145l74 26h11q-52 -199 -80 -347q-8 -39 6 -39q7 0 32 17.5t47 39.5z" id="x1D462"></path></g>
</svg> and <svg height="7.9499998" id="M284" 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
q13 -21 0 -43z" id="x1D45F"></path></g>
</svg> express the results base on user communities in Figures <a href="../fig2/">2</a> and <a href="../fig3/">3</a>, respectively.</table>

The Scientific World Journal

A Collaborative Recommend Algorithm Based on Bipartite Community

Figure 4