Abstract
The mobile and handheld devices have become an indispensable part of life in this era of technological advancement. Further, the ubiquity of location acquisition technologies like global positioning system (GPS) has opened the new avenues for location aware applications for mobile devices. Reading online news is becoming increasingly popular way to gather information from news sources around the globe. Users can search and read the news of their preference wherever they want. The news preferences of individuals are influenced by several factors including the geographical contexts and the recent trends on social media. In this work we propose an approach to recommend the personalized news to the users based on their individual preferences. The model for user preferences are learned implicitly for individual users. Also, the popularity of trending articles floating around the twitter are exploited to provide news interesting recommendations to the user. We believe that the interest of the user, popularity of article and other attributes of news are implicitly fuzzy in nature and therefore we propose to exploit this for generating the recommendation score for articles to be recommended. The prototype is developed for testing and evaluation of proposed approach and the results of the evaluation are motivating.
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References
Abel, F., Gao, Q., Houben, G.-J., Tao, K.: Analyzing user modeling on twitter for personalized news recommendations. In: Konstan, Joseph A., et al. (eds.) UMAP 2011. LNCS, vol. 6787, pp. 1–12. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-22362-4_1
Adomavicius, G., Mobasher, B., Ricci, F., Tuzhilin, A.: Context-aware recommender systems. AI Mag. 32(3), 67–80 (2011)
Adomavicius, G., Tuzhilin, A.: Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Trans. Know. Data Eng. (IEEE) 17(6), 734–749 (2005)
Berjani, B., Strufe, T.: A recommendation system for spots in location-based online social networks. In: Proceedings of the 4th Workshop on Social Network Systems, Salzburg, Austria. ACM (2011)
Burke, R.: Hybrid recommender systems: survey and experiments. User Model. User-Adap. Inter. 12(4), 331–370 (2002)
Billsus, D., Pazzani, Michael J.: A hybrid user model for news story classification. In: Kay, J. (ed.) UM99 User Modeling. CICMS, vol. 407, pp. 99–108. Springer, Vienna (1999). https://doi.org/10.1007/978-3-7091-2490-1_10
Bomhardt, C.: NewsRec, a SVM-driven personal recommendation system for news websites. In: Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence, pp. 545–548. IEEE Computer Society, September 2004
Cantador, I., Bellogín, A., Castells, P.: Ontology-based personalised and context-aware recommendations of news items. In: IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2008, vol. 1, pp. 562–565. IEEE, December 2008
Gemmell, J., Shepitsen, A., Mobasher, B., Burke, R.: Personalization in folksonomies based on tag clustering. In: Intelligent Techniques for Web Personalization & Recommender Systems, vol. 12 (2008)
IJntema, W., Goossen, F., Frasincar, F., Hogenboom, F.: Ontology-based news recommendation. In: Proceedings of the 2010 EDBT/ICDT Workshops, p. 16. ACM, March 2010
Jonnalagedda, N., Gauch, S.: Personalized news recommendation using twitter. In: 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), vol. 3, pp. 21–25. IEEE, November 2013
Lee, H.J., Park, S.J.: MONERS: a news recommender for the mobile web. Expert Syst. Appl. 32(1), 143–150 (2007)
Li, L., Chu, W., Langford, J., Schapire, R.E.: A contextual-bandit approach to personalized news article recommendation. In: Proceedings of the 19th International Conference on World Wide Web, pp. 661–670. ACM, April 2010
Liang, T.P., Lai, H.J.: Discovering user interests from web browsing behavior: an application to internet news services. In: Proceedings of the 35th Annual Hawaii International Conference on System Sciences, HICSS, pp. 2718–2727. IEEE, January 2002
Liu, J., Dolan, P., Pedersen, E.R.: Personalized news recommendation based on click behavior. In: Proceedings of the 15th International Conference on Intelligent User Interfaces, pp. 31–40. ACM, February 2010
Phelan, O., McCarthy, K., Smyth, B.: Using twitter to recommend real-time topical news. In: Proceedings of the Third ACM Conference on Recommender Systems, pp. 385–388. ACM, October 2009
Phelan, O., McCarthy, K., Bennett, M., Smyth, B.: Terms of a feather: content-based news recommendation and discovery using Twitter. In: Clough, P., et al. (eds.) ECIR 2011. LNCS, vol. 6611, pp. 448–459. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-20161-5_44
Tiwari, S., Kaushik, S.: Modeling personalized recommendations of unvisited tourist places using genetic algorithms. In: Chu, W., Kikuchi, S., Bhalla, S. (eds.) DNIS 2015. LNCS, vol. 8999, pp. 264–276. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-16313-0_20
Tiwari, S., Kaushik, S.: Evolving recommendations from past travel sequences using soft computing techniques. Int. J. Comput. Sci. Eng. 14(3), 242–254 (2017)
Tiwari, S., Kaushik, S., Jagwani, P.: Location based recommender systems: architecture, trends and research areas (2012)
Tiwari, S., Kaushik, S.: Mining popular places in a geo-spatial region based on GPS data using semantic information. In: Madaan, A., Kikuchi, S., Bhalla, S. (eds.) DNIS 2013. LNCS, vol. 7813, pp. 262–276. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-37134-9_20
Tiwari, S., Kaushik, S.: Information enrichment for tourist spot recommender system using location aware crowdsourcing. In: 2014 IEEE 15th International Conference on Mobile Data Management (MDM), vol. 2, pp. 11–14. IEEE, July 2014
Tiwari, S., Kaushik, S.: A non functional properties based web service recommender system. In: 2010 International Conference on Computational Intelligence and Software Engineering (CiSE), pp. 1–4. IEEE, December 2010
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Tiwari, S., Pangtey, M.S., Kumar, S. (2018). Location Aware Personalized News Recommender System Based on Twitter Popularity. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2018. ICCSA 2018. Lecture Notes in Computer Science(), vol 10963. Springer, Cham. https://doi.org/10.1007/978-3-319-95171-3_51
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DOI: https://doi.org/10.1007/978-3-319-95171-3_51
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