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Analyzing Topics and Trends in the PRIMA Literature

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PRIMA 2016: Principles and Practice of Multi-Agent Systems (PRIMA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9862))

Abstract

This study investigates the content of the literature published in the proceedings of the International Conference on Principles and Practices of Multi-Agent Systems (PRIMA). Our study is based on a corpus of the 611 papers published in eighteen PRIMA proceedings from 1998 (when the conference started) to 2015. We have developed an unsupervised topic model, using Latent Dirichlet Allocation (LDA), over the PRIMA corpus of papers to analyze popular topics in the literature published at PRIMA in the past eighteen years. We have also analyzed historical trends and examine the strength of each topic over time.

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Notes

  1. 1.

    The conference’s abbreviation is still PRIMA.

  2. 2.

    https://pdfbox.apache.org.

References

  1. Anthes, G.: Topic models vs. unstructured data. Commun. ACM 53(12), 16–18 (2010)

    Article  Google Scholar 

  2. Battisti, F., Ferrara, A., Salini, S.: A decade of research in statistics: a topic model approach. Scientometrics 103(2), 413–433 (2015)

    Article  Google Scholar 

  3. Blei, D.M., Lafferty, J.D.: Dynamic topic models. In: Proceedings of the 23rd International Conference on Machine Learning, ICML 2006, pp. 113–120. ACM, New York (2006)

    Google Scholar 

  4. Blei, D.M., Lafferty, J.D.: Topic models, pp. 71–94. CRC Press (2009)

    Google Scholar 

  5. Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent dirichlet allocation. J. Mach. Learn. Res. 3, 993–1022 (2003)

    MATH  Google Scholar 

  6. Brner, K., Chen, C., Boyack, K.W.: Visualizing knowledge domains. Ann. Rev. Inf. Sci. Technol. 37(1), 179–255 (2003)

    Article  Google Scholar 

  7. Chen, C.: Citespace II: detecting and visualizing emerging trends and transient patterns in scientific literature. J. Am. Soc. Inf. Sci. Technol. 57(3), 359–377 (2006)

    Article  Google Scholar 

  8. Cox, A.S.D.R.: Some quick sign tests for trend in location and dispersion. Biometrika 42(1/2), 80–95 (1955)

    Article  MathSciNet  MATH  Google Scholar 

  9. Geman, S., Geman, D.: Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Trans. Pattern Anal. Mach. Intell. 6(6), 721–741 (1984)

    Article  MATH  Google Scholar 

  10. Hall, D., Jurafsky, D., Manning, C.D.: Studying the history of ideas using topic models. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, EMNLP 2008, pp. 363–371. Association for Computational Linguistics, Stroudsburg (2008)

    Google Scholar 

  11. Liu, P., Jameel, S., Lam, W., Ma, B., Meng, H.M.: Topic modeling for conference analytics. In: INTERSPEECH 2015, 16th Annual Conference of the International Speech Communication Association, Dresden, Germany, 6–10 September 2015, pp. 707–711 (2015)

    Google Scholar 

  12. Mann, G.S., Mimno, D., McCallum, A.: Bibliometric impact measures leveraging topic analysis. In: Proceedings of the 6th ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL 2006, pp. 65–74. ACM, New York (2006)

    Google Scholar 

  13. McCallum, A.K.: MALLET: a machine learning for language toolkit (2002). http://mallet.cs.umass.edu

  14. Neff, M.W., Corley, E.A.: 35 years and 160, 000 articles: a bibliometric exploration of the evolution of ecology. Scientometrics 80(3), 657–682 (2009)

    Article  Google Scholar 

  15. Petruzzi, P.E., Busquets, D., Pitt, J.: Experiments with social capital in multi-agent systems. In: Dam, H.K., Pitt, J., Xu, Y., Governatori, G., Ito, T. (eds.) PRIMA 2014. LNCS, vol. 8861, pp. 18–33. Springer, Heidelberg (2014)

    Google Scholar 

  16. Popa, T., Rebedea, T., Chiru, C.: Detecting and describing historical periods in a large corpora. In: 26th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2014, Limassol, Cyprus, 10–12 November 2014, pp. 764–770 (2014)

    Google Scholar 

  17. Raulamo-Jurvanen, P., Mäntylä, M.V., Garousi, V.: Citation, topic analysis of the ESEM papers. In: 2015 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM 2015, Beijing, China, 22–23 October 2015, pp. 136–139 (2015)

    Google Scholar 

  18. Steyvers, M., Griffiths, T.: Latent semantic analysis: a road to meaning. In: Chapter Probabilistic Topic Models. Lawrence Erlbaum (2007)

    Google Scholar 

  19. Wallach, H.M., Murray, I., Salakhutdinov, R., Mimno, D.: Evaluation methods for topic models. In: Proceedings of the 26th Annual International Conference on Machine Learning, ICML 2009, pp. 1105–1112. ACM, New York (2009)

    Google Scholar 

  20. Wang, X., McCallum, A.: Topics over time: a non-Markov continuous-time model of topical trends. In: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2006, pp. 424–433. ACM, New York (2006)

    Google Scholar 

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Author information

Authors and Affiliations

  1. School of Computing and Information Technology, University of Wollongong, Wollongong, NSW, 2522, Australia

    Hoa Khanh Dam & Aditya Ghose

Authors
  1. Hoa Khanh Dam
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  2. Aditya Ghose
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Corresponding author

Correspondence to Hoa Khanh Dam .

Editor information

Editors and Affiliations

  1. Dipartimento di Informatica, Università degli Studi di Torino , Torino, Italy

    Matteo Baldoni

  2. Computing and Communications, Lancaster University, Lancaster, United Kingdom

    Amit K. Chopra

  3. Department of Computer Science, New Mexico State University, Las Cruces, New Mexico, USA

    Tran Cao Son

  4. Graduate School of Maritime Sciences, Kobe University, Kobe, Japan

    Katsutoshi Hirayama

  5. Dept. di Informatica: Sci. e Ingegneria, Universitá di Bologna, Bologna, Italy

    Paolo Torroni

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© 2016 Springer International Publishing Switzerland

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Dam, H.K., Ghose, A. (2016). Analyzing Topics and Trends in the PRIMA Literature. In: Baldoni, M., Chopra, A., Son, T., Hirayama, K., Torroni, P. (eds) PRIMA 2016: Principles and Practice of Multi-Agent Systems. PRIMA 2016. Lecture Notes in Computer Science(), vol 9862. Springer, Cham. https://doi.org/10.1007/978-3-319-44832-9_13

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  • DOI: https://doi.org/10.1007/978-3-319-44832-9_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44831-2

  • Online ISBN: 978-3-319-44832-9

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