FLY: Venue recommendation using limited context

Sailaja Rajanala, Manish Singh

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

3 Citations (Scopus)

Abstract

Recommendation of publication venues is very much the need of the hour. There is a sea of options for research conferences and journals. As a result, it is often found that researchers are not even aware of many publication venues in their research area. Existing work uses information, such as all the references in a given paper, past publication venues of the author(s), co-Author relationships, and the paper content to do venue recommendation. However, in this paper, we propose a system that uses very limited context, namely the paper title, abstract, and a venue network, which is constructed using only a small subset of authors' publication history, to do venue recommendation. Our venue recommendation system, FLY, gives 30% higher accuracy compared to the current state-of-The-Art limited context venue recommendation system.

Original languageEnglish
Title of host publicationProceedings - IEEE 32nd International Conference on Tools with Artificial Intelligence, ICTAI 2020
EditorsMiltos Alamaniotis, Shimei Pan
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages200-204
Number of pages5
ISBN (Electronic)9781728192284
ISBN (Print)9781728185361
DOIs
Publication statusPublished - 2020
Externally publishedYes
EventInternational Conference on Tools with Artificial Intelligence 2020 - Online, Baltimore, United States of America
Duration: 9 Nov 202011 Nov 2020
Conference number: 32nd
https://ieeexplore.ieee.org/xpl/conhome/9288160/proceeding (Proceedings)

Conference

ConferenceInternational Conference on Tools with Artificial Intelligence 2020
Abbreviated titleICTAI 2020
Country/TerritoryUnited States of America
CityBaltimore
Period9/11/2011/11/20
Internet address

Keywords

  • Citation Network
  • Topic Modeling
  • Venue Recommendation

Cite this