Classification algorithms for interactive multimedia services: a review

被引：0
作者：
Chun-Wei Tsai
Ming-Yi Liao
Chu-Sing Yang
Ming-Chao Chiang
机构：
[1] Chia Nan University of Pharmacy & Science,Department of Applied Geoinformatics
[2] National Cheng Kung University,Institute of Computer and Communication Engineering, Department of Electrical Engineering
[3] National Sun Yat-sen University,Department of Computer Science and Engineering
来源：
Multimedia Tools and Applications | 2013年 / 67卷
关键词：
Interactive multimedia service; Clustering; Classification;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Interactive multimedia services, which integrate and unify techniques from a variety of disciplines, have been an active research topic for many years. However, two major challenges need to be overcome to provide a better service: The first is that interactive multimedia systems have to provide the contents a user needs at the right time no matter where the user is located and what device the user is using; the second is that the performance of such systems needs to be improved. Apparently, classification and clustering (also called unsupervised classification) algorithms play an indispensable role in these respects. Thus, this paper contains a review of the classification algorithms for interactive multimedia systems. Also discussed in this paper are several important issues, open questions, and trends.
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页码：137 / 165
页数：28
相关论文
共 228 条
  • [1] Ahanger G(1996)A survey of technologies for parsing and indexing digital video J Vis Commun Image Represent 7 28-43
  • [2] Little TDC(1998)The interactive multimedia jukebox (imj): a new paradigm for the on-demand delivery of audio/video Comput Netw Isdn Syst 30 431-441
  • [3] Almeroth KC(2008)A relevance feedback CBIR algorithm based on fuzzy sets Image Commun 23 490-504
  • [4] Ammar MH(2010)The internet of things: a survey Comput Networks 54 2787-2805
  • [5] Arevalillo-Herráez M(2001)An interactive multimedia system on “computer architecture, organization, and design” IEEE Trans Ed 44 41-46
  • [6] Zacarés M(2008)A non-supervised approach for repeated sequence detection in TV broadcast streams Signal Process Image Commun 23 525-537
  • [7] Benavent X(2009)TV program recommendiation for groups based on multidimensional TV-anytime classifications IEEE Trans Consum Electron 55 1-2
  • [8] de Ves E(2003)Metaheuristics in combinatorial optimization: overview and conceptual comparison ACM Comput Surv 35 268-308
  • [9] Atzori L(2010)Natale FGBD A stochastic approach to image retrieval using relevance feedback and particle swarm optimization IEEE Trans Multimedia 12 267-277
  • [10] Iera A(2002)Kernel methods: a survey of current techniques Neurocomputing 48 63-84
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