Abstract
Selecting a good conference or journal in which to publish a new article is very important to many researchers and scholars. The choice of publication venue is usually based on the author’s existing knowledge of publication venues in their research domain or the match of the conference topics with their paper content. They may not be aware of new or other more appropriate conference venues to which their paper could be submitted. A traditional way to recommend a conference to a researcher is by analyzing her paper and comparing it to the topics of different conferences using content-based analysis. However, this approach can make errors due to mismatches caused by ambiguity in text comparisons. In this paper, we present a new approach allowing researchers to automatically find appropriate publication venues for their research paper by exploring author’s network of related co-authors and other researchers in the same domain. This work is a part of our social network based recommendation research for research publications venues and interesting hot-topic researches. Experiments with a set of ACM SIG conferences show that our new approach outperforms the content-based approach and provides accurate recommendation. This works also demonstrates the feasibility of our ongoing approach aimed at using social network analysis of researchers and experts in the relevant research domains for a variety of recommendation tasks.
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Luong, H., Huynh, T., Gauch, S., Do, L., Hoang, K. (2012). Publication Venue Recommendation Using Author Network’s Publication History. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Intelligent Information and Database Systems. ACIIDS 2012. Lecture Notes in Computer Science(), vol 7198. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28493-9_45
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DOI: https://doi.org/10.1007/978-3-642-28493-9_45
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