Community Clustering Algorithm in Complex Networks Based on Microcommunity Fusion

<div>Experimental comparison of each of the <svg height="9.49473pt" id="M155" style="vertical-align:-0.2063999pt" version="1.1" viewbox="-0.0498162 -9.28833 7.55047 9.49473" width="7.55047pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M547 100L523 123C489 76 461 62 452 62C442 62 433 71 427 109C405 243 387 408 378 495C360 666 322 710 263 710C230 710 182 688 161 667L170 639C184 646 203 651 218 651C247 651 272 634 288 562C297 521 300 485 304 436C230 267 111 104 24 11L33 -12L116 6C163 73 263 255 311 362L347 84C355 26 373 -12 406 -12C440 -12 489 12 547 100Z" id="g50-233"></path><glyph.data ascent="3443" descent="-2856" horiz-adv-x="571" vert-adv-y="571"></glyph.data></g></svg> in data set of Karate Network data set.</div>

Mathematical Problems in Engineering

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Figure 8

Figure 8: Community Clustering Algorithm in Complex Networks Based on Microcommunity Fusion 