Indicator Selection for Topic Popularity Definition Based on AHP and Deep Learning Models

<table class="table-group" id="tab19"><tr><td><table class="table"><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr class="thead"><td class="align_left">Case no.</td><td class="align_center">Characteristic description</td></tr><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td class="align_left">1</td><td class="align_center">RNN</td></tr><tr><td class="align_left">2</td><td class="align_center">LSTM</td></tr><tr><td class="align_left">3</td><td class="align_center">GRU</td></tr><tr><td class="align_left">4</td><td class="align_center">AHP-based <svg height="12.5794pt" id="M48" style="vertical-align:-3.29107pt" version="1.1" viewbox="-0.0498162 -9.28833 222.984 12.5794" width="222.984pt" 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="M689 332C689 394 670 448 646 448C620 448 597 421 597 396C597 386 600 381 608 372C619 359 620 334 620 315C620 150 538 45 454 45C414 45 386 67 386 122C386 138 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Discrete Dynamics in Nature and Society

tab19

Table 19

Table 19: Indicator Selection for Topic Popularity Definition Based on AHP and Deep Learning Models 