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020 _a9783030233501
_9978-3-030-23350-1
024 7 _a10.1007/978-3-030-23350-1
_2doi
050 4 _aTK5105.5-5105.9
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072 7 _aCOM043000
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082 0 4 _a004.6
_223
100 1 _aWei, Xin.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aMultimedia QoE Evaluation
_h[electronic resource] /
_cby Xin Wei, Liang Zhou.
250 _a1st ed. 2019.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2019.
300 _aX, 82 p. 37 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Computer Science,
_x2191-5776
505 0 _a1 Introduction -- 2 Technical Premise -- 3 Multimedia Service Data Preprocessing and Feature Extraction -- 4 Multimedia QoE Modeling and Prediction -- 5 Implementation and Demonstration -- 6 Conclusion.
520 _aThis SpringerBrief discusses the most recent research in the field of multimedia QoE evaluation, with a focus on how to evaluate subjective multimedia QoE problems from objective techniques. Specifically, this SpringerBrief starts from a comprehensive overview of multimedia QoE definition, its influencing factors, traditional modeling and prediction methods. Subsequently, the authors introduce the procedure of multimedia service data collection, preprocessing and feature extractions. Then, describe several proposed multimedia QoE modeling and prediction techniques in details. Finally, the authors illustrate how to implement and demonstrate multimedia QoE evaluation in the big data platform. This SpringerBrief provides readers with a clear picture on how to make full use of multimedia service data to realize multimedia QoE evaluation. With the exponential growth of the Internet technologies, multimedia services become immensely popular. Users can enjoy multimedia services from operators or content providers by TV, computers and mobile devices. User experience is important for network operators and multimedia content providers. Traditional QoS (quality of service) can not entirely and accurately describe user experience. It is natural to research the quality of multimedia service from the users’ perspective, defined as multimedia quality of experience (QoE). However, multimedia QoE evaluation is difficult, because user experience is abstract and subjective, hard to quantify and measure. Moreover, the explosion of multimedia service and emergence of big data, all call for a new and better understanding of multimedia QoE. This SpringerBrief targets advanced-level students, professors and researchers studying and working in the fields of multimedia communications and information processing. Professionals, industry managers, and government research employees working in these same fields will also benefit from this SpringerBrief.
650 0 _aComputer networks .
650 0 _aArtificial intelligence.
650 1 4 _aComputer Communication Networks.
650 2 4 _aArtificial Intelligence.
700 1 _aZhou, Liang.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030233495
776 0 8 _iPrinted edition:
_z9783030233518
830 0 _aSpringerBriefs in Computer Science,
_x2191-5776
856 4 0 _uhttps://doi.org/10.1007/978-3-030-23350-1
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c173101
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