{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T22:55:18Z","timestamp":1771023318866,"version":"3.50.1"},"reference-count":28,"publisher":"IEEE","license":[{"start":{"date-parts":[[2017,11,1]],"date-time":"2017-11-01T00:00:00Z","timestamp":1509494400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2017,11,1]],"date-time":"2017-11-01T00:00:00Z","timestamp":1509494400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,11]]},"DOI":"10.1109\/nof.2017.8251212","type":"proceedings-article","created":{"date-parts":[[2018,1,11]],"date-time":"2018-01-11T18:39:01Z","timestamp":1515695941000},"page":"1-7","source":"Crossref","is-referenced-by-count":19,"title":["Improving QoE prediction in mobile video through machine learning"],"prefix":"10.1109","author":[{"given":"Pedro","family":"Casas","sequence":"first","affiliation":[{"name":"AIT Austrian Institute of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sarah","family":"Wassermann","sequence":"additional","affiliation":[{"name":"Universit&#x00E9; de Li&#x00E8;ge"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/2398776.2398799"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/2785971.2785978"},{"key":"ref12","article-title":"Quantification of You Tube QoE via Crowdsourcing","author":"ho\u00dffeld","year":"2011","journal-title":"IEEE International Symposium on Multimedia"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/2018602.2018611"},{"key":"ref14","article-title":"Initial Delay vs. Interruptions: Between the Devil and the Deep Blue Sea","author":"ho\u00dffeld","year":"2012","journal-title":"QoMEX"},{"key":"ref15","article-title":"Assessing Effect Sizes of Influence Factors Towards a QoE Model for HTTP Adaptive Streaming","author":"ho\u00dffeld","year":"2014","journal-title":"QoMEX"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/2535372.2535394"},{"key":"ref17","article-title":"YOUQMON: A System for On-line Monitoring of YouTube QoE in Operational 3G Networks","volume":"41","author":"casas","year":"2013","journal-title":"ACM SIGMETRICS PER"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/2940136.2940137"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/2789168.2795176"},{"key":"ref28","author":"duda","year":"2000","journal-title":"Pattern classification 2nd edition"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2016.2537645"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/2565585.2565600"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2014.2360940"},{"key":"ref6","article-title":"Tech. report 2017","author":"nam","year":"0","journal-title":"YouSlow What Influences User Abandonment Behavior for Internet Video?"},{"key":"ref5","article-title":"YoMo: A YouTube Application Comfort Monitoring Tool","author":"staehle","year":"2010","journal-title":"Qoemc"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/2663716.2663726"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/2534169.2486025"},{"key":"ref2","year":"1996","journal-title":"ITU-T Rec P 800 Methods for subjective determination of transmission quality"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/2043164.2018478"},{"key":"ref1","year":"2017","journal-title":"Cisco Visual Networking Index Global Mobile Data Traffic Forecast Update 20122017 Cisco White Paper"},{"key":"ref20","article-title":"Induction of Model Trees for Predicting Continuous Classes","author":"wang","year":"1997","journal-title":"ECML"},{"key":"ref22","author":"ghadiyaram","year":"2016","journal-title":"LIVE Mobile Stall Video Database"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/GlobalSIP.2014.7032269"},{"key":"ref24","article-title":"A Time-varying Subjective Quality Model for Mobile Streaming Videos with Stalling Events","author":"ghadiyaram","year":"2015","journal-title":"SPIE Optical Engineering+ Applications"},{"key":"ref23","first-page":"264","article-title":"Internet Video Delivery in YouTube: From Traffic Measurements to Quality of Experience","volume":"7754","author":"ho\u00dffield","year":"2013","journal-title":"Data Traffic Monitoring and Analysis From Measurement Classification and Anomaly Detection to Quality of Experience"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/QoMEX.2017.7965687"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2014.7025402"}],"event":{"name":"2017 8th International Conference on the Network of the Future (NOF)","location":"London, UK","start":{"date-parts":[[2017,11,22]]},"end":{"date-parts":[[2017,11,24]]}},"container-title":["2017 8th International Conference on the Network of the Future (NOF)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8239402\/8251204\/08251212.pdf?arnumber=8251212","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,12]],"date-time":"2025-08-12T17:57:33Z","timestamp":1755021453000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8251212\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,11]]},"references-count":28,"URL":"https:\/\/doi.org\/10.1109\/nof.2017.8251212","relation":{},"subject":[],"published":{"date-parts":[[2017,11]]}}}