User Value Identification Based on Improved RFM Model and <span class="nowrap"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.06580067pt" id="M1" height="11.4652pt" version="1.1" viewBox="-0.0657574 -11.3994 13.1359 11.4652" width="13.1359pt"><g transform="matrix(.017,0,0,-0.017,0,0)"><path id="g113-76" d="M743 650H503L496 622L527 618C563 613 564 603 532 573C449 495 371 431 323 392C301 374 272 355 246 346L280 522C297 609 300 614 379 622L385 650H135L129 622C209 614 215 609 198 522L124 133C106 39 99 35 23 28L17 0H271L277 28C193 35 192 39 208 133L239 316C264 328 280 325 303 288C368 183 435 90 502 0H652L659 28C602 34 584 43 543 94C495 154 403 283 347 369L574 554C634 603 659 612 735 624L743 650Z"/></g></svg>-</span>Means++ Algorithm for Complex Data Analysis

<table class="table-group" id="tab6"><tr><td><table class="table"><tr><td class="thead-hr" colspan="6"><hr/></td></tr><tr class="thead"><td class="align_left">Cluster</td><td class="align_center"><span style="width: 12.0767ptpx;"><svg height="11.6425pt" id="M125" style="vertical-align:-0.2063999pt" version="1.1" viewbox="-0.0498162 -11.4361 12.0767 11.6425" width="12.0767pt" 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="M610 18C585 26 567 34 540 68C517 97 499 128 476 171C452 215 425 276 413 304C496 332 570 394 570 494C570 555 545 595 509 619S419 650 364 650H139L133 622C216 615 219 612 203 527L129 132C112 40 105 36 23 28L17 0H279L285 28C199 34 194 40 211 132L239 284H284C320 284 334 275 351 236C374 182 394 140 420 93C459 23 495 -1 592 -8H600L610 18ZM480 485C480 424 449 372 403 342C374 323 338 316 293 316H245L291 562C296 589 301 601 311 608S337 618 358 618C432 618 480 575 480 485Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,8.151,-5.741)"><path d="M310 541L304 571C290 586 211 619 185 610L80 76L131 52L310 541Z"></path></g></svg></span></td><td class="align_center"><span style="width: 11.8158ptpx;"><svg height="11.4859pt" id="M126" style="vertical-align:-0.04979992pt" version="1.1" viewbox="-0.0498162 -11.4361 11.8158 11.4859" width="11.8158pt" 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="M584 650H137L131 622C214 614 217 612 200 521L125 127C109 41 101 35 23 28L17 0H288L294 28C201 35 193 42 209 128L242 309H348C440 309 442 300 443 226H471L510 422H482C452 354 449 348 357 348H251L295 575C302 609 304 615 338 615H426C502 615 517 604 526 581C534 560 536 524 537 492L565 494C574 554 583 631 584 650Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,7.895,-5.741)"><path d="M310 541L304 571C290 586 211 619 185 610L80 76L131 52L310 541Z"></path></g></svg></span></td><td class="align_center"><span style="width: 16.7482ptpx;"><svg height="11.4859pt" id="M127" style="vertical-align:-0.04979992pt" version="1.1" viewbox="-0.0498162 -11.4361 16.7482 11.4859" width="16.7482pt" 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="M962 650H795L470 145L347 650H176L170 622C268 613 275 606 244 503L190 322C150 188 132 126 118 91C102 50 80 33 18 28L12 0H245L251 28C175 35 170 48 174 93C177 128 191 180 220 284L292 542H294C331 392 383 150 409 4H432L774 555H776L714 137C700 40 694 34 612 28L606 0H868L874 28C793 34 784 37 797 137L849 533C859 612 863 616 956 622L962 650Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,12.807,-5.741)"><path d="M310 541L304 571C290 586 211 619 185 610L80 76L131 52L310 541Z"></path></g></svg></span></td><td class="align_center">Count</td><td class="align_center">Value ranking</td></tr><tr><td class="thead-hr" colspan="6"><hr/></td></tr><tr><td class="align_left">Cluster 1</td><td class="align_center">0.1474</td><td class="align_center">0.1622</td><td class="align_center">0.2849</td><td class="align_center">34</td><td class="align_center">1</td></tr><tr><td class="align_left">Cluster 3</td><td class="align_center">0.1135</td><td class="align_center">0.0792</td><td class="align_center">0.1202</td><td class="align_center">106</td><td class="align_center">2</td></tr><tr><td class="align_left">Cluster 4</td><td class="align_center">0.1165</td><td class="align_center">0.0192</td><td class="align_center">0.0324</td><td class="align_center">188</td><td class="align_center">3</td></tr><tr><td class="align_left">Cluster 2</td><td class="align_center">0.0293</td><td class="align_center">0.0152</td><td class="align_center">0.0225</td><td class="align_center">252</td><td class="align_center">4</td></tr><tr class="table-tr"><td colspan="6"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>RFM model customer segmentation value analysis.</div>

Wireless Communications and Mobile Computing

tab6

Table 6

Table 6: User Value Identification Based on Improved RFM Model and <span class="nowrap"><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" style="vertical-align:-0.06580067pt" id="M1" height="11.4652pt" version="1.1" viewBox="-0.0657574 -11.3994 13.1359 11.4652" width="13.1359pt"><g transform="matrix(.017,0,0,-0.017,0,0)"><path id="g113-76" d="M743 650H503L496 622L527 618C563 613 564 603 532 573C449 495 371 431 323 392C301 374 272 355 246 346L280 522C297 609 300 614 379 622L385 650H135L129 622C209 614 215 609 198 522L124 133C106 39 99 35 23 28L17 0H271L277 28C193 35 192 39 208 133L239 316C264 328 280 325 303 288C368 183 435 90 502 0H652L659 28C602 34 584 43 543 94C495 154 403 283 347 369L574 554C634 603 659 612 735 624L743 650Z"/></g></svg>-</span>Means++ Algorithm for Complex Data Analysis 

Wireless Communications and Mobile Computing

User Value Identification Based on Improved RFM Model and -Means++ Algorithm for Complex Data Analysis

Table 6