BEGIN:VCALENDAR VERSION:2.0 PRODID:-//hacksw/handcal//NONSGML v1.0//EN METHOD:PUBLISH BEGIN:VEVENT DTSTAMP:20240329T014844Z DESCRIPTION:Click for Latest Location Information: http://graphorum2019.dat aversity.net/sessionPop.cfm?confid=132&proposalid=10997\n
Immigration is a hot topic, as it evokes images of the “wall” and immigrants f looding our borders; however, immigration also affects business, academics, religion, and tourism. Public perception correlates &l dquo;immigration” with “illegality.” As there a re over 100 non-immigrant legal visa categories, and nine million non- immigrant visas are issued annually, tens of thousands of dollars are spent to navigate the process to enter the USA.
\nOur presentation fo cuses on graph-based text analytics to decrease the probability of app lication denial. The process of applying, obtaining, and entering in on&nbs p;L-1 status costs upwards of $5,000 USD, and routinely takes three to four months for a decision. Further, USCIS's Request for Evidence (RFE) requires the petitioner to prepare evidentiary documentation, t hereby escalating costs and time. Our use of text analytics increase the pr obability of obtaining an approved petition. We isolate the specific use of words to promote an approved application. We construct and store graph-based document-term matrices (DTM) from petitions and then fit a model to the corpus leveraging classification to improve direct peti tion acceptance.
\n\n Immigration to the U.S. is a costly and challenging process.\n Metadata extracted from immigration visas can improve the probability petit ion acceptance.\n Analysis using statistics and regression allows the most savvy applicants a n advantage.\n\n DTSTART:20191016T161500 SUMMARY:Using Graph Theory to Scale the Border Wall to Legal U.S. Status DTEND:20191016T171459 LOCATION: See Description END:VEVENT END:VCALENDAR