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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References
Klamma, R., Cuong, P.M., Cao, Y.: You never walk alone: recommending academic events based on social network analysis. In: Proceedings of the First International Conference on Complex Science, Complex 2009, pp. 657–670 (2009)
Boukhris, I., Ayachi, R.: A novel personalized academic venue hybrid recommender. In: IEEE 15th International Symposium on Computational Intelligence and Informatics, CINTI, pp. 465–470 (2014)
Pham, M.C., Cao, Y., Klamma, R., Jarke, M.: A clustering approach for collaborative filtering recommendation using social network analysis. J. Univ. Comput. Sci. 17(4), 583–604 (2011)
Yang, Z., Davison, B.D.: Venue recommendation: submitting your paper with style. In: Proceedings of the 11th International Conference on Machine Learning and Applications, ICMLA 2012, pp. 681–686 (2012)
Kang, N., Doornenbal, M.A., Schijvenaars, R.J.A.: Elsevier journal finder: recommending journals for your paper. In: Proceedings of the 9th ACM Conference on Recommender Systems, RecSys 2015, pp. 261–264 (2015)
Kucuktunc, O., Saule, E., Kaya, K., Catalyurek, U.V.: The advisor: a webservice for academic recommendation. In: Proceedings of the 13th ACM IEEE - CS Joint Conference on Digital Libraries, JCDL 2013, pp. 433–434 (2013)
Alhoori, H., Furuta, R.: Recommendation of scholarly venues based on dynamic user interests. J. Informetrics 11(2), 553–563 (2017)
Ricci, F., Rokach, L., Shapira, B., Kantor, P.B.: Recommender Systems Handbook (2011)
Luong, H., Huynh, T., Gauch, S., Hoang, K.: Exploiting social networks for publication venue recommendations. In: International Conference on Knowledge Discovery and Information Retrieval, KDIR 2012, pp. 239–245 (2012)
García, G.M., Nunes, B.P., Lopes, G.R., Casanova, M.A., Paes Leme, L.A.P.: Techniques for comparing and recommending conferences. J. Brazil. Comput. Soc. (2017)
Bobadilla, J., Ortega, F., Hernando, A., Gutierrez, A.: Recommender systems survey. Knowl.-Based Syst. 46, 109–132 (2013)
Park, Y., Park, S., Jung, W., Lee, S.G.: Reversed CF: a fast collaborative filtering algorithm using a k-nearest neighbor graph. Expert Syst. Appl. 42(8), 4022–4028 (2015)
Su, X., Khoshgoftaar, T.M.: A survey of collaborative filtering techniques. Adv. Artif. Intell. 2009, 1–19 (2009)
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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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