Download Advances in Electronic Commerce, Web Application and by Yan-qing Chen, Jian-min Qi, Ling-juan Shi (auth.), David PDF

By Yan-qing Chen, Jian-min Qi, Ling-juan Shi (auth.), David Jin, Sally Lin (eds.)

ECWAC2012 is an built-in convention dedicated to digital trade, net software and communique. within the this lawsuits you will find the conscientiously reviewed medical final result of the second one overseas convention on digital trade, net program and verbal exchange (ECWAC 2012) held at March 17-18,2012 in Wuhan, China, bringing jointly researchers from all over the international within the field.

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Extra resources for Advances in Electronic Commerce, Web Application and Communication: Volume 1

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So the video feature space can be seen as a tensor which constitutes three vectors. We can formally denote it as: Ψ ∈ ℜ W o rd O B JE C T , W o rd A S R , W o rd V O C R (1) In the optimization procedure, we check every word in every modal. If a word is far away from the other two modal’s words in semantic relation measure, in other words, if there are no corresponding words in the other two modals, so this word is isolated and will be dropped off. Though the above procedure is simple and comprehensible, the computation complexity is terrible.

23–27. com © Springer-Verlag Berlin Heidelberg 2012 24 S. Zhang, H. Li, and S. Zhang real world videos are shown in Section 5. We end the paper with a conclusion and some prospective future work in Section 6. 1 Optimization Problem Through above analysis, the video is represented by three high level semantic feaText ASR , Text VOCR and Text OBJECT . They can be seen as tures, namely the three sub spaces of the video high level feature space. The three folds of texts can be processed by part of speech and stemming, and only the noun words are kept to form three bags of words.

Every undirected edge with weight w in the original graph is replaced by two directed edges with weight w. An edge from the source to every vertex in G is added with weight m’= ΣeєE(G) w(e), where E(G) is the set of all edges in G and w(e) is the weight of edge e. An edge from every vertex in G to the sink is added with weight m’ + 2g – di, where g is a guess of the density of the densest A Foreground Segmentation Scheme 25 sub graph and di is the sum of all weights of edges in G adjacent to vertex i.

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