@techreport{TD:100518,
	att_abstract={{In large-scale IPTV systems, it is essential to
maintain high service quality while providing a wider variety
of service features than typical traditional TV. Thus
service quality assessment systems are of paramount importance
as they monitor the user-perceived service quality and
alert when issues occurs. For IPTV systems, however, there
is no simple metric to represent user-perceived service quality
and Quality of Experience (QoE).Moreover, there is only
limited user feedback, often in the form of noisy and delayed
customer complaints. Therefore, we aim to approximate the
QoE through a selected set of performance indicators in a
proactive (i.e., detect issues before customers complain) and
scalable fashion.
In this paper, we present service quality assessment framework,
Q-score, which accurately learns a small set of performance
indicators most relevant to user-perceived service
quality, and proactively infers service quality in a single score.
We evaluate Q-score using network data collected from a
commercial IPTV service provider and show that Q-score is
able to predict 60% of service problems that are complained
by customerswith 0.1%of false positives. ThroughQ-score,
we have (i) gained insight into various types of service problems
causing user dissatisfaction includingwhy users tend to
react promptly to sound issues while late to video issues; (ii)
identified and quantified the opportunity to proactively detect
the service quality degradation of individual customers
before severe performance impact occurs; and (iii) observed
possibility to adaptively allocate customer care workforce to
potentially troubling service areas.}},
	att_authors={jw2129, zg2325, jy1348, am649n, ab0762, mc4381},
	att_categories={},
	att_copyright={{ACM}},
	att_copyright_notice={{(c) ACM, 2011. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Internet Measurement Conference. {{, 2011-11-02}}.
}},
	att_donotupload={},
	att_private={false},
	att_projects={},
	att_tags={},
	att_techdoc={true},
	att_techdoc_key={TD:100518},
	att_url={http://web1.research.att.com:81/techdocs_downloads/TD:100518_DS1_2011-09-16T02:54:37.348Z.pdf},
	author={Jia Wang and Zihui Ge and Jennifer Yates and Ajay Mahimkar and Andrea Basso and Min-hsuan Chen and Han Hee Song and Yin Zhang},
	institution={{ACM Internet Measurement Conference}},
	month={November},
	title={{Q-score: Proactive Service Quality Assessment in a Large IPTV System}},
	year=2011,
}