Abstract
Publishing scientific results is extremely important for each researcher. The concrete challenge is how to select the right academic venue that corresponds to researcher’s current interest and without missing the deadline at the same time. Due to the huge number of academic venues especially in the field of computer science, it is difficult for researchers to choose a conference or a journal to submit their works. A lot of time is wasted asking about the conference topics, its host country, its ranking, its submission deadline, etc. To tackle this problem, this paper proposes a recommendation approach that suggests personalized upcoming academic venues to computer scientists that fit their current research area and also their interests in terms of venue location and ranking. The target researcher and his community current preferences are taken into consideration. Experiments demonstrate the effectiveness of our proposed rating and recommendation method and show that it outperforms the baseline venue recommendations in terms of accuracy and ranking quality.
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Mhirsi, N., Boukhris, I. (2018). Exploring Location and Ranking for Academic Venue Recommendation. In: Abraham, A., Muhuri, P., Muda, A., Gandhi, N. (eds) Intelligent Systems Design and Applications. ISDA 2017. Advances in Intelligent Systems and Computing, vol 736. Springer, Cham. https://doi.org/10.1007/978-3-319-76348-4_9
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DOI: https://doi.org/10.1007/978-3-319-76348-4_9
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