سیستم پیشنهاد دهنده خبر آگاه بر مکان با استفاده از منطق فازی

نوع مقاله: مقاله پژوهشی

نویسندگان

1 کارشناس ارشد - گروه مهندسی کامپیوتر، دانشکده مهندسی، واحد مشهد، دانشگاه آزاد اسلامی، مشهد، ایران

2 استادیار - باشگاه پژوهشگران جوان و نخبگان، واحد مشهد، دانشگاه آزاد اسلامی، مشهد، ایران

3 استادیار - گروه مهندسی کامپیوتر، دانشکده مهندسی، واحد مشهد، دانشگاه آزاد اسلامی، مشهد، ایران

چکیده

با انتشار حجم عظیمی از خبرها بر روی اینترنت و تمایل بیشتر کاربران به سرویس‌های خبری تحت وب، نیاز به یک سیستم پیشنهاد دهنده خبر ضروری می‌باشد. خبرها برای آنکه قابل توجه باشند سرویس‌های خبری از تعدادی معیار به نام ارزش‌ خبر استفاده می‌کنند و مکان کاربر نقش موثری در بررسی این معیارها دارد. در این مقاله LONEF یک سیستم پیشنهاد دهنده خبر با ساختار دو مرحله ارائه شده است. در مرحله اول با توجه به مکان کاربران، خبرها اولویت‌دهی می‌شوند و مرحله دوم با در نظر گرفتن خصوصیاتی همچون اولویت مکانی، تازگی ، اعتبار منبع خبر ، اولویت گروهی و محبوبیت، خبرها پیشنهاد داده می‌شوند. برای کاهش ابهامات این خصوصیات از دو سیستم در منطق فازی شامل استنتاج فازی ممدانی و تصمیم گیری مبتنی بر مورد استفاده شده است. در سیستم استنتاج فازی ممدانی سعی شده است با بهینه سازی در انتخاب قوانین و توابع عضویت سرعت سیستم بهبود داده ‌شود و همچنین به علت پیاده‌سازی‌ مبهم بازخوردهای کاربران در پیشنهاد دهنده‌های موجود یک سیستم تصمیم گیری بکار رفته شده است تا بتوان رفتار کاربران را بهتر بازنمایی کرد. میزان کارایی دیدگاه ارائه شده در این پژوهش از طریق نتایج آزمایش‌های مختلف بر روی مجموعه خبری نمایش داده شده است.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Location-aware News Recommendation System with Using Fuzzy Logic

نویسندگان [English]

  • Mehdi Nejati 1
  • Hamid Tabatabaee 2
  • Mehrdad Jalali 3
1 MSc – Department of Computer Engineering, Islamic Azad University, Mashhad Branch, Mashhad, Iran
2 Assistant Professor - young researcher club, Islamic Azad University, Mashhad Branch, Mashhad, Iran
3 Assistant Professor - Department of Computer Engineering, Islamic Azad University, Mashhad Branch, Mashhad, Iran
چکیده [English]

with release of a huge amount of news on the Internet and the trend of users to Web-based news services.it is necessary to have a recommendation system. To grab attentions to news, news services use a number of criteria that called news values and user location is an important factor for it. In this paper, LONEF is proposed as a tow stage recommendation system. In first stage news are ranked by user’s locations and in second stage news are recommended by location Preferences, recency, Trustworthiness, groups priorities and popularity. To reduce ambiguity these properties is used tow Mamdani fuzzy interference and case-based decision systems. In Mamdani fuzzy interference system, it is tried to increase the system speed by optimizing selection of rules and membership functions and because of ambiguous feedback implementation, a decision making system is used to enable better simulation of user’s activities. Performance of our proposed approach is demonstrated in the experiments on different news groups.

کلیدواژه‌ها [English]

  • News Recommendation systems
  • News Recommendation
  • Fuzzy logic
  • location-aware Recommendation
[1] M. Balabanovic, Y. Shoham, "Content-based, collaborative recommendation," in Communications of the ACM, 1997.

[2] O. pencer-Thomas, "Writing a press release.," 2012. [Online]. Available: http://www.owenspencer- thomas.com/journalism/media-tips/writing-a-press-release. [Accessed 8 August 2015].

[3] F. Filloux, "Google News: the secret sauce," the guardian, 25 February 2013. [Online]. Available: http://www.theguardian.com/technology/2013/feb/25/1. [Accessed 18 8 2015].

[4] A. Montes-García, J.M. Álvarez-Rodríguez, J.E. Labra-Gayo, M. Martínez-Merino, "Towards a journalist-based news recommendation system: The Wesomender approach," Expert Systems with Applications, Vol. 40, pp. 6735-6741, 2013.

[5] T. Bilgiç, I. Turksen, "Measurement of membership functions: theoretical and empirical work," In Fundamentals of Fuzzy Sets: Handbook of Fuzzy Sets and Systems, Boston, Dubois,D;, 2000, p. 195–232.

[6] D. Jurafsky, J. Martin, speech and language processing, new jersey: prenticce Hall, 2014.

[7] T. Hofmann, "Probabilistic latent semantic indexing," in In Proceedings of the 22nd annual international ACM SIGIR conference on research and development in information retrieval. SIGIR ’99, New York, NY, USA: ACM., 1999.

[8] D.M. Blei, A. Ng, M.I. & Jordan, "Latent Dirichlet allocation," Journal of Machine Learning Research, vol. 3, p. 993–1022, 2003.

[9] D. Billsus, M. Pazzani, "A personal news agent that talks, learns and explains," Proceedings of the third annual conference on Autonomous Agents, pp. 268-275, 1999.

[10] L. Li, D. Wang, T. Li, D. Knox, B. Padmanabhan, "SCENE: a scalable two-stage personalized news recommendation system.," Sigir, pp. 125-134, 2011.

[11] L. Zheng, L. Li, W. Hong, T. Li, "PENETRATE: Personalized news recommendation using ensemble hierarchical clustering," Expert Systems with Applications, Vol. 40, pp. 2127-2136, 2013.

[12] H.J. Lee, S.J. Park, "MONERS: A news recommender for the mobile web," Expert Systems with Applications, Vol. 32, No. 1, pp. 143-150, 2007.

[13] R.R. Yager, "Fuzzy logic methods in recommender systems," Fuzzy Sets and Systems, Vol. 136, No. 2, pp. 133-149, 2003.

[14] P. Perny, J.-d. Zucker, "Collaborative Filtering Methods based on Fuzzy Preference Relations," In Proceedings of EUROFUSE-SIC, 1999.

[15] C. Cornelis, J. Lu, X. Guo, G. Zhang, "One-and-only item recommendation with fuzzy logic techniques," Information Sciences, Vol. 177, No. 22, pp. 4906-4921, 2007.

[16] A. Tejeda-Lorente, J. Bernabé-Moreno, C. Porcel, E. Herrera-Viedma, "Integrating quality criteria in a fuzzy linguistic recommender system for digital libraries," Procedia Computer Science, Vol. 31, pp. 1036-1043, 2014.

[17] B.A. Ojokoh, M.O. Omisore, O.W. Samuel, T.O. Ogunniyi, "A Fuzzy Logic Based Personalized Recommender System," in International Journal of Computer Science and Information Technology & Security (IJCSITS), 2012.

[18] A. Zenebe, A.F. Norcio, "Representation, similarity measures and aggregation methods using fuzzy sets for content-based recommender systems," Fuzzy Sets and Systems, Vol. 160, No. 1, pp. 76-94, 2009.

[19] M.N.M. Adnan, M.R. Chowdury, I. Taz, T. Ahmed, R.M. Rahman, "Content based news recommendation system based on fuzzy logic," in 2014 International Conference on Informatics, Electronics & Vision (ICIEV), 2014.

[20] J.J. Levandoski, M. Sarwat, A. Eldawy, M.F. Mokbel, "LARS: A location-aware recommender system," in Proceedings - International Conference on Data Engineering, 2012.

[21] L.M. de Campos, J.M. Fernández-Luna, J.F. Huete, "A collaborative recommender system based on probabilistic inference from fuzzy observations," Fuzzy Sets and Systems, Vol. 159, No. 12, pp. 1554-1576, 2008.

[22] C.P. Pappis, N.I. Karacapilidis, "A comparative assessment of measures of similarity of fuzzy values," Fuzzy Sets and Systems, pp. 171-174, 1993.

[23] Z.M, H.N, "Avoiding monotony: improving the diversity of recommendation lists," In Proceedings of the ACM Conference on Recommender Systems, 2008.

[24] L. Zadeh, "Fuzzy Sets," Inform.Control 8, p. 338–353, 1965.

[25] L. Li, W. Chu, "A Contextual-Bandit Approach to Personalized News Article Recommendation," In WWW , 2010.