Authoritative Venues

dc.contributor.authorYoussef, Alien
dc.contributor.authorMarku, Bellaen
dc.contributor.authorSpicer, Tanneren
dc.contributor.authorForst, Kyleen
dc.date.accessioned2021-05-13T17:25:59Zen
dc.date.available2021-05-13T17:25:59Zen
dc.date.issued2021en
dc.description.abstractThis submission details the progress made on the Authoritative Venues project. The goal of the Authoritative Venues project was to use machine learning algorithms to create a web application that can accurately recommend fitting ACM-related venues for Computer Science researchers trying to publish their work. By providing a ranked output list of publication venues related to a paper’s topic, we help researchers make more informed decisions about where to submit their work for publication. Additionally, we provide insight into the data collection, virtual machine setup, and website hosting process that allowed for this project to be easily accessible by anyone. This project is particularly useful for CS researchers wanting to gain insight into which ACM-related publication venue would best fit their paper. The recommender is hosted at authvenue.cs.vt.edu. On this website, there are two input fields that researchers can use to provide the title and abstract of their paper. Once this is inputted, researchers can submit this information and receive recommendations specifically catered to their work.en
dc.description.notesAuthoritativeVenuesReport.pdf is the final report of the Authoritative Venues project. It cannot be edited. AuthoritativeVenuesPresentation.pdf is the final presentation of the Authoritative Venues project. It cannot be edited. AuthoritativeVenuesReport.docx is an editable version of the Authoritative Venues final report. AuthoritativeVenuesPresentation.pptx is an editable version of the Authoritative Venues final presentation.en
dc.identifier.urihttp://hdl.handle.net/10919/103266en
dc.language.isoen_USen
dc.publisherVirginia Techen
dc.subjectVenue Recommenderen
dc.subjectAuthoritative Venuesen
dc.subjectVenuesen
dc.subjectMachine learningen
dc.subjectACM Venuesen
dc.subjectACMen
dc.subjectResearch Paperen
dc.subjectComputer Science Researchen
dc.titleAuthoritative Venuesen
dc.typePresentationen
dc.typeReporten

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