Abstract
In this paper, we outline our effort to enhance the page-view rates of e-content that online customers read on a popular portal in Greece. The portal, athensvoice.gr, provides continuous coverage on news, politics, science, the arts, and opinion columns and its customers generate approximately 6 million unique visits per month. Gains both in terms of advertisement and further e-content market penetration were the objectives of our effort which yielded the PolyRecs system, in production for more than a year now. In designing PolyRecs, we were primarily concerned with the use of pages in real-time and to this end, we elected to utilize five key criteria to achieve the aforementioned goals. We selected criteria for which we were able to obtain pertinent statistics without compromising performance and offered a real-time exploitation of the user page-views on the go. In addition, we were keen in realizing not only effective on-the-fly calculations of what might be interesting to the browsing individuals at specific points in time but also produce accurate results capable of improving the user-experience. The key factors exploited by PolyRecs entail features from both collaboration and content-based systems. Once operational, PolyRecs helped the news portal attain an average increase of 6.3% of the overall page-views in its traffic. To ascertain the PolyRecs utility, we provide a brief economic analysis in terms of measured performance indicators and identify the degree of contribution each of the key factors offers. Last but not least, we have developed PolyRecs as a domain-agnostic hybrid-recommendation system for we wanted it to successfully function regardless of the underlying data and/or content infrastructure.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
McCreadie, R., Macdonald, C., Ounis, I.: News vertical search: when and what to display to users. In: Proceedings of 36th International ACM SIGIR Conference, Dublin, Ireland (2013)
Wang, J., de Vries, A.P., Reinders, M.J.T.: Unifying user-based and item-based collaborative filtering approaches by similarity fusion. In Proceedings of 29th International ACM SIGIR Conference, Seattle, WA, August 2006
Liu, J., Dolan, P., Pedersen, E.R.: Personalized news recommendation based on click behavior. In: Proceedings of 15th International Conference on Intelligent User Interfaces (IUI), Hong Kong, PR China (2010)
Maksai, A., Garcin, F., Faltings, B.: Predicting online performance of news recommender systems through richer evaluation metrics. In: Proceedings of 9th ACM RecSys Conference, New York, NY (2015)
Lu, Z., Dou, Z., Lian, J., Xie, X., Yang, Q.: Content-based collaborative filtering for news topic recommendation. In: AAAI Conference, February 2015
Yi, X., Hong, L., Zhong, E., Liu, N.-N., Rajan, S.: Beyond Clicks: dwell time for personalization. In: Proceedings of 8th ACM RecSys Conference, Foster City, CA (2014)
Weinsberg, U., Bhagat, S., Ioannidis, S., Taft, N.: Inferring and obfuscating user gender based on ratings. In: Proceedings of 6th ACM RecSys Conference, Barcelona, Spain, September 2012
Schmidt, K., Bächle, S., Scholl, P., Nold, G.: Big scale text analytics and smart content navigation. In: Castellanos, M., Dayal, U., Pedersen, T.B., Tatbul, N. (eds.) BIRTE 2013-2014. LNBIP, vol. 206, pp. 167–170. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-46839-5_12
Das, A.S., Datar, M., Garg, A., Rajaram, S.: Google news personalization: scalable online collaborative filtering. In Proceedings of the 16th International Conference on World Wide Web, Banff, Canada (2007)
Garcin, F., Faltings, B., Donatsch, O., Alazzawi, A., Bruttin, C., Huber, A.: Offline and online evaluation of news recommender systems at swissinfo.ch. In: Proceedings of 8th ACM Conference on RecSys, Foster City, CA (2014)
Zhang, W., Wang, J., Chen, B., Zhao, X.: To personalize or not: a risk management perspective. In: Proceedings of 7th ACM RecSys Conference, Hong Kong, China (2013)
Wu, X., et al.: Personalized next-song recommendation in online karaokes. In: Proceedings of 7th ACM RecSys Conference, Hong Kong, PR China, October 2013
Vargas, S., Castells, P.: Rank and relevance in novelty and diversity metrics for recommender systems. In: Proceedings of 5th ACM RecSys Conference, Chicago, IL (2011)
Garcin, F., Dimitrakakis, C., Faltings, B.: Personalized news recommendation with context trees. In: Proceedings of 7th ACM RecSys Conference, Hong Kong, China (2013)
Diaz, F.: Integration of news content into web results. In: Proceedings of 2nd ACM International Conference on WSDM, Barcelona, Spain, pp. 182–191 (2009)
König, A.C., Gamon, M., Wu, Q.: Click-through prediction for news queries. In: Proceedings of the 32nd International ACM SIGIR Conference, Boston, MA, pp. 347–354 (2009)
Arguello, J., Diaz, F., Callan, J., Crespo, J.-F.: Sources of evidence for vertical selection. In: Proceedings of 32nd International ACM SIGIR Conference, pp. 315–322, Boston, MA (2009)
Said, A., Bellogin, A., Lin, J., de Vries, A.: Do recommendations matter?: news recommendation in real life. In: Computing of 17th ACM Conference on CSCW on Social Computing, Baltimore, MD, pp. 237–240 (2014)
Gebremeskel, G., de Vries, A.P.: The degree of randomness in a live recommender systems evaluation. In: Working Notes, Conference and Labs of the Evaluation Forum (CLEF), Toulouse, France, September 2015
Song, Y., Ma, H., Wang, H., Wang, K.: Exploring and exploiting user search behavior on mobile and tablet devices to improve search relevance. In: Proceedings of 22nd International WWW Conference, Rio de Janeiro, Brazil, pp. 1201–1212. ACM (2013)
Acknowledgements
we are grateful for the reviewer comments received; partial support for this work has been provided by the GALENA EU Project and Google.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Papakonstantinou, M., Delis, A. (2019). PolyRecs: Improving Page–View Rates Using Real-Time Data Analysis. In: Castellanos, M., Chrysanthis, P., Pelechrinis, K. (eds) Real-Time Business Intelligence and Analytics. BIRTE BIRTE BIRTE 2015 2016 2017. Lecture Notes in Business Information Processing, vol 337. Springer, Cham. https://doi.org/10.1007/978-3-030-24124-7_7
Download citation
DOI: https://doi.org/10.1007/978-3-030-24124-7_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-24123-0
Online ISBN: 978-3-030-24124-7
eBook Packages: Computer ScienceComputer Science (R0)